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Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform. This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness. You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact. This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging. What you'll do: Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field. Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance. Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization. Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale learning and serving: storage/retrieval for embeddings, feature pipelines, and APIs. Collaborate with ML/Ranking infra to ensure low-latency serving, high availability, and integration with MLOps systems. Drive Cross-Team Integration & Impact: Partner with Feeds, Notification, Search and Ads teams to drive experimentation and adoption of new user understanding models with product teams across Reddit, ensuring measurable end-to-end impact on key metrics. Set Technical Bar & Mentor: Mentor senior to staff engineers, lead design reviews, steward technical decisions across the user understanding domain, and champion and drive engineering processes and best practices Who you might be: You have at least 10 years experience building and scaling production-grade ML systems, particularly in user modeling, large-scale representation learning, or recommender systems. You have a track record of driving ambiguous, high-impact initiatives from concept to production, shaping both technical direction and execution. You are product- and impact-oriented: you care deeply about how your work moves real metrics (e.g., engagement, retention, revenue), not just model quality. You bring strong fundamentals in mainstream user understanding ML approaches (e.g., representation learning, behavioral modeling, user clustering), and understand their trade-offs in real-world systems. You are excited about the GenAI shift and have experience (or strong intuition) applying LLMs or foundation models to evolve existing systems,  going beyond incremental improvements. You think in systems, not just models: you consider data, training, evaluation, serving, and adoption as a cohesive whole, and design with end-to-end impact in mind. You influence beyond your immediate team: partnering effectively with product, infra, and other ML teams, and driving alignment across multiple stakeholders. You raise the technical bar: mentoring senior engineers, leading design reviews, and establishing best practices for building reliable, scalable ML systems. You are comfortable navigating trade-offs across quality, latency, cost, and safety, especially in large-scale, user-facing systems. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-remote, #LI-JS5 Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $266,000 — $372,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Задачи: — Build high-quality software products with attention to detail and craftsmanship. — Work on real-world projects that have measurable impact. — Collaborate closely within an engineering team focused on growth-oriented solutions. — Take ownership from concept through delivery ensuring robustness at every stage. Требования: — Mastery of C# — Strong computer science fundamentals including best practices, design principles, algorithms and data structures. — .NET Core proficiency — JavaScript/TypeScript expertise — Concurrency understanding.

Location: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. About the Role We are at an inflection point where AI is fundamentally reshaping what products can do and how users experience them. We're not just looking for a product manager — we're looking for a hybrid product builder who truly understands AI capabilities and can translate technical potential into real user value. You will lead end-to-end product design for LLM / Agent-powered applications — from zero to one — across domains including intelligent customer service, personalized recommendations, AI assistants, and automated workflows. You are the critical connector between user insights, AI technical capabilities, and business objectives: someone who can discuss RAG retrieval strategies and multi-agent orchestration with ML engineers, while clearly articulating product value and delivery roadmaps to business stakeholders. If you have genuine passion for AI-native products and the ability to define clear product direction amid ambiguity and rapid change, we'd love to build the next generation of AI applications together. Key Responsibilities End-to-End AI Product Lifecycle Management Own the full product lifecycle of AI applications — including intelligent chatbots, AI assistants, recommendation systems, and automated workflows — from requirements definition and product design through to launch and delivery. Produce high-quality PRDs, interaction flow diagrams, and acceptance criteria while driving cross-functional teams to execute efficiently. LLM / Agent Capability Productization Deeply engage in Agent product design, including task planning workflows, tool-calling strategies (Function Calling / MCP), context management mechanisms, multi-agent orchestration logic, and graceful failure/fallback handling. Translate underlying model capabilities into meaningful, perceivable user value. AI Evaluation Framework & Quality Standards Build Harness evaluation frameworks for AI products — designing test scenario sets, evaluation metric systems (accuracy, hallucination rate, task completion rate, etc.), and regression test case libraries. Independently assess AI capability boundaries and drive continuous model iteration and product quality improvement. Conversational Product Design & Knowledge Engineering Lead platform architecture planning for intelligent customer service and conversational assistant products, covering knowledge base structure design, dialogue flow and SOP design, corpus annotation and training strategy, intelligent reply generation, and case summarization. Leverage large-scale data analysis to continuously optimize conversation quality and issue resolution rates. Personalization Engines & Generative UI Products Collaborate deeply with ML and data teams to design recommendation strategies that deliver truly personalized, individualized user experiences. Define generative UI product requirements and drive growth in core business metrics including CTR, conversion rate, and user retention. Establish comprehensive attribution analysis frameworks for recommendation effectiveness. AI Capability Integration with Business Scenarios Develop a thorough understanding of business goals and user pain points. Proactively identify opportunities to apply AI technologies — including RAG, Prompt Engineering, and multimodal capabilities — to concrete use cases. Define clear product evolution roadmaps that balance technical feasibility, user experience, and commercial value. Cross-Functional Collaboration & AI-Native Product Culture Act as the product Owner in close collaboration with algorithm, engineering, data, design, operations, and business teams. Maintain a strong sense of ownership in a fast-moving AI-native environment, continuously track industry developments, and rapidly translate emerging AI capabilities into product innovation opportunities. Requirements Product Experience : 3+ years of product management experience, with at least 1 year of direct hands-on experience delivering AI application products, AIGC products, or Agent products. Must have fully shipped at least one AI-related feature module or standalone product. AI Technical Understanding : Deep understanding of the productization of mainstream AI technologies, including but not limited to: LLM Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, Agent fundamentals (tool calling / task planning / context window management), and conversational system design. Ability to independently evaluate the product feasibility of technical proposals. Evaluation & Data Capabilities : Proven ability to design AI product evaluation frameworks — independently defining evaluation metrics, building test case sets, and tracking product performance through data analysis. Familiarity with A/B experiment design and a strong data-driven decision-making mindset. Documentation & Communication Skills : Ability to write structured, logically rigorous PRDs, technical requirement documents, and flow diagrams. Excellent cross-functional communication skills with the ability to accurately bridge information between technical and business teams, eliminating information gaps. User Insight & Product Thinking : Sharp ability to translate ambiguous user needs into clearly defined product requirements. Skilled at finding the right product balance between AI capability boundaries and user expectations — avoiding both overpromising and underutilizing model capabilities. Learning Agility & Ownership Mindset : Sustained enthusiasm and capacity for continuous learning in a rapidly evolving AI landscape. Strong sense of ownership — able to proactively define problems, drive decisions, and take accountability for outcomes in highly ambiguous environments. Nice to Have Familiarity with cutting-edge AI engineering practices including MCP ( Model Context Protocol ), Function Calling, and multi-agent orchestration frameworks (e.g., LangChain / AutoGen / CrewAI), enabling deep technical dialogue with engineering teams. Experience with AI Harness / Eval / Benchmark platform product design or usage, with involvement in establishing and maintaining LLM evaluation systems. Background in Fintech / e-commerce / SaaS industries, with an understanding of the unique product design requirements for AI in high-concurrency, compliance-sensitive environments. Bilingual fluency in Chinese and English (spoken and written), with the ability to independently drive product collaboration and cross-cultural communication within international teams. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial We are building for the >80% of economic activity that happens beyond the reach of screens. AI has learned from the text, images and video online, but it still lacks an accurate understanding of physical space. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Senior/Staff Product Engineer to join our Embodied AI team. Working alongside the group's GM, Product leader, and robot learning engineer, you'll own how the product reaches customers, build the integrations that make it native to their simulators and deployment stacks, and influence the roadmap. You've turned capabilities into products. You've shipped developer-facing products and watched adoption turn on details nobody planned for. You know that a capability isn't a product until someone outside the building has used it without help, and you're passionate about the work that sits between the two. This is not a role for someone who wants to manage and not ship, or someone who wants to ship without ownership of commercial consequences. This is a role for an entrepreneurial engineer who loves to build and is energized by making the people around them, researchers and customers alike, more effective. You have a co-founder mentality. You may have been part of a founding team before, or want to start your own business one day. What You'll Do - Build the Product Surface - Own how autonomy teams experience our work: the APIs, UIs, packages, and documentation. - Make Our World Native to the Customer's - Turn scans and reconstructions into reliable, interoperable assets that work in customers' simulation tools and workflows, including packaging, metadata, semantic labels, object structure, and selectable variants. - Turn Prototypes Into Capability - Partner with reconstruction, mapping, localization, and research teams to transform prototypes and pipeline outputs into production-grade services and user experiences. - Deliver at Scale - Design and operate backend systems for accounts, organizations, sites, scans, assets, processing jobs, permissions, asynchronous workflows, storage, and data access. - Make It Work - Work directly with customers and internal users to integrate our technology, diagnose failures, improve reliability, and close the gap between intended and actual product behavior. - Influence the Roadmap - Work alongside the group's GM, Product leader, and robot learning engineer to shape what we build and when. What You'll Bring - 6+ years of software engineering experience; Bachelor's degree in Computer Science or a related field, or equivalent practical experience. - Significant experience building and operating production web applications and backend services, with strong fundamentals in API design, data modeling, testing, observability, and reliability. - Shipped developer-facing products — including the documentation and reference code external engineers actually used — and worked with 3D asset formats or comparable binary formats to production depth: you can say what the conventions were, where they broke, and what it cost you. - Proficient in Python and TypeScript, comfortable working across frontend and backend, and able to take a feature from product requirements through to running it in production. - Experience designing asynchronous workflows, long-running jobs, external integrations, and data-intensive systems. Nice to Have - Experience working with robotics simulators or toolchains such as Isaac Sim, Isaac Lab, or MuJoCo, or OpenUSD. - Built products for geospatial, 3D, computer vision, graphics, robotics, or spatial computing. - Worked on visualization or asset-management experiences with React, Next.js, or Three.js. Competencies - Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it. - Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular. - Pragmatic. You have no patience for not-invented-here syndrome and analysis paralysis. You find the fastest path to a working capability without one-way doors that undermine scaling. - Confident and credible with customers. You can read an autonomy engineer's training config, find why our asset didn't load, and explain the fix in their terms. - Fluent in other people's ecosystems. You'll spend much of your time learning new tools and stacks. You're quick to learn the customer's language, and you can point to something you shipped in a world that was foreign to you a quarter earlier. Compensation & Benefits The base salary range for this role is $207,000 - $265,000, and your offer within it will reflect your experience and the scope you take on. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: New York, United States Who We Are At OKX, we believe the future will be reshaped by crypto and blockchain technology. We operate a leading global crypto platform and build products and services designed to expand access to the digital-asset ecosystem. Across our global organization, we value ownership, sound judgment, collaboration, innovation, and the ability to operate effectively in a fast-moving and continuously evolving environment. Recruiting should insert the current approved OKX corporate “Who We Are” language when the position is posted. About the Team The Fraud Investigations Team (FIT) is a First Line of Defense function within OKX’s Risk organization responsible for identifying, assessing, investigating, and helping manage significant internal and external fraud risks affecting the company, its customers, personnel, and operations. FIT conducts and supports complex investigations involving digital assets, internal and external fraud, employee misconduct, insider threats, unauthorized access or misuse of information, vendor and third-party misconduct, account compromise, social engineering, collusion, conflicts of interest, and other significant fraud-related matters. The team works closely with Legal, HR, Information Security,Engineering, Physical Security, Compliance, Finance, Operations, and other functions across OKX. About the Opportunity We are looking for an experienced Senior Analyst, Blockchain Investigations & Fraud Intelligence to join FIT. This is first and foremost a blockchain investigations role requiring significant hands-on expertise tracing digital assets across complex blockchain ecosystems. The successful candidate must be capable of independently conducting sophisticated on-chain investigations, developing and testing attribution hypotheses, identifying relationships among wallets and entities, following assets through multiple chains and protocols, and translating highly technical blockchain activity into clear investigative findings. Blockchain analysis is a specialized investigative discipline. Accordingly, we are seeking someone who understands not only how to operate commercial tracing platforms, but also the underlying blockchain architecture, transactional mechanics, attribution methodologies, clustering techniques, tracing limitations, and evidentiary considerations necessary to reach reliable conclusions. The role extends beyond on-chain analysis. The Senior Analyst will combine blockchain intelligence with enterprise data, system logs, transactional records, open-source information, and other evidence to support complex fraud and insider-risk investigations. The position will also provide analytical support to the Global Physical Security Team (PST) on selected protective-intelligence and threat-assessment matters. The Senior Analyst will directly manage one Analyst and will be expected to serve as a subject-matter resource for blockchain investigations and analytical methodology across FIT. What You’ll Be Doing Blockchain Investigations & Digital-Asset Intelligence Lead and conduct complex blockchain investigations and transaction tracing across multiple wallets, counterparties, entities, blockchains, tokens, protocols, and digital-asset ecosystems. Trace the origin, movement, conversion, layering, consolidation, and ultimate disposition of digital assets , including activity spanning multiple intermediaries and blockchain environments. Conduct investigations using tools such as Chainalysis Reactor , TRM Labs, Elliptic, or comparable blockchain intelligence platforms , while understanding the methodologies and limitations underlying platform-generated attribution. Analyze activity involving centralized exchanges, self-hosted wallets, decentralized exchanges, cross-chain bridges, mixers, privacy-enhancing technologies, DeFi protocols, smart contracts, stablecoins, NFTs, OTC activity, gambling platforms, and other relevant ecosystems . Trace assets across multiple chains and cross-chain transactions , identifying continuity of funds where technically supportable and clearly documenting assumptions or limitations where definitive attribution is not possible. Analyze transaction graphs, address relationships, behavioral patterns, clusters, counterparties, timing, amounts, transaction sequencing, and other relevant blockchain indicators. Understand and appropriately apply wallet-clustering and attribution methodologies , including the limitations and potential for false attribution associated with particular heuristics. Independently evaluate blockchain intelligence rather than relying solely on automated labels, risk scores, or vendor-generated attribution. Corroborate on-chain findings, where appropriate, with internal account records, KYC / KYB information, transaction data, access information, open-source intelligence, legal-process returns, or other available evidence . Identify relationships among blockchain addresses, OKX accounts, external counterparties, individuals, organizations, vendors, affiliates, and other relevant entities. Reconstruct complex transaction flows and create clear fund-flow diagrams, transaction maps, timelines, and visualizations that allow investigators and nontechnical stakeholders to understand the movement of assets. Analyze blockchain activity associated with suspected fraud , theft, account takeover, social engineering, insider activity, collusion, payment diversion, asset misappropriation, or other misconduct . Identify new wallets, counterparties, entities, or transactional patterns that may generate additional investigative leads. Clearly document the methodology, assumptions, confidence level, and limitations associated with blockchain findings. Distinguish between confirmed attribution , vendor attribution, analytical inference, behavioral similarity, and an unverified investigative hypothesis . Avoid presenting blockchain proximity, exposure, clustering, or a commercial risk score alone as proof of ownership, control, intent, or misconduct. Maintain current knowledge of emerging blockchain technologies, protocols, tracing methodologies, obfuscation techniques, fraud typologies, and developments affecting blockchain attribution or investigations . Fraud Investigations & Investigative Intelligence Conduct and support investigations involving internal and external fraud , employee misconduct, insider threats, vendor and third-party misconduct, collusion, conflicts of interest, asset misappropriation, unauthorized access, credential misuse, and other significant fraud risks . Combine blockchain findings with off-chain evidence to develop a comprehensive investigative picture rather than treating blockchain activity in isolation . Develop investigative hypotheses and objectively test those hypotheses against available evidence, including information that supports, contradicts, or fails to establish the hypothesis. Conduct timeline reconstruction, link analysis, relationship mapping, pattern analysis, clustering, and comparative analysis across individuals, accounts, wallets, devices, systems, transactions, and entities. Support investigations involving account takeover, impersonation, social engineering, business-email compromise, payment diversion, affiliate misconduct, and trusted-party abuse , particularly where a digital-asset, employee, vendor, or enterprise nexus exists. Analyze vendor, affiliate, partner, and other third-party activity for indicators of billing irregularities, undisclosed relationships, conflicts of interest, unusual payments, control circumvention, or other potential misconduct. Support investigative interviews by developing transaction timelines, identifying inconsistencies or information gaps, organizing evidence, and identifying appropriate areas for follow-up. Enterprise Data & Insider-Risk Analytics Analyze appropriately authorized information including system and access logs, authentication records, audit trails, customer-account activity, KYC / KYB information, transaction records, payment information, case-management records, vendor information, and relevant security telemetry . Correlate blockchain activity with enterprise data to identify possible connections among wallets, accounts, employees, customers, vendors, devices, transactions, and other relevant entities . Support investigations involving suspected unauthorized access, information misuse or exfiltration, credential compromise, control circumvention, unauthorized disclosure, or abuse of privileged access. Identify anomalous behavior or access patterns that may warrant additional investigation. Develop repeatable analytical methodologies capable of processing and correlating information from disparate systems. Use appropriate scripting, database querying, data visualization, and analytical technologies to efficiently analyze large or complex datasets. Investigative Reporting & Evidence Prepare clear, concise, and well-supported blockchain investigation reports, investigative memoranda, executive summaries, transaction-flow diagrams, link charts, timelines, and other analytical products . Explain complex blockchain concepts and transaction activity in plain language suitable for investigators, senior management, Legal, regulators, or law enforcement , as appropriate. Clearly distinguish among allegations, investigative leads, known facts, third-party attribution , analytical judgments, assumptions, information gaps, and substantiated conclusions . Ensure analytical conclusions are proportionate to the evidence and do not imply greater certainty than the underlying blockchain or other data supports. Maintain sufficient documentation to allow significant blockchain findings to be reviewed, reproduced, and understood by another qualified analyst . Preserve and handle investigative records in accordance with applicable evidence-preservation, chain-of-custody, confidentiality, privacy, access-control, and need-to-know requirements . Support appropriately authorized law-enforcement, regulatory, litigation, or legal matters in coordination with the appropriate company functions. Protective Intelligence & Physical Security Support Provide analytical support to PST on selected matters involving threats or concerning activity directed toward employees, executives, offices, events, or other company interests. Conduct authorized open-source, link, timeline, blockchain, financial, or other analytical research where relevant to understanding the identity, relationships, capabilities, or activity associated with a potential threat. Assist in evaluating available information relating to credibility, corroboration, intent, capability, access or opportunity, targeting, escalation, timing, and other relevant indicators . Prepare objective analytical products identifying known facts, analytical judgments, material information gaps, uncertainties, and appropriate confidence levels. Support PST’s assessment while preserving PST’s responsibility for protective-security decisions and operational response . Leadership & Development Directly manage and develop one Junior Analyst, including work allocation, coaching, technical development, quality assurance, and review of analytical work product . Serve as a FIT subject-matter resource for blockchain investigations and on-chain analytical methodology . Review blockchain analysis for technical accuracy, appropriate methodology, corroboration, reasonable attribution, and evidentiary support. Train and mentor junior personnel in transaction tracing, blockchain intelligence platforms, analytical reasoning, documentation, and investigative methodology. Help establish consistent standards for blockchain investigations, attribution , documentation, quality assurance, and reporting . Participate in time-sensitive investigations affecting a global organization, including occasional work outside normal business hours when required. What We Look For In You 7+ years of relevant investigative or analytical experience , with meaningful professional experience specifically conducting cryptocurrency or blockchain investigations . Demonstrated hands-on expertise independently conducting complex blockchain tracing investigations , rather than solely reviewing blockchain alerts or commercial risk scores. Advanced proficiency with one or more blockchain intelligence platforms such as Chainalysis Reactor , TRM Labs, Elliptic, or comparable technology . Strong understanding of how blockchain intelligence platforms derive attribution, clustering, exposure, and risk information—and the limitations associated with those methodologies . Demonstrated understanding of blockchain fundamentals, including wallets and addresses, transactions, UTXO and account-based models, tokens, smart contracts, block explorers, transaction fees, confirmations, and blockchain-specific transactional structures . Strong understanding of digital-asset ecosystems including centralized exchanges, self-hosted wallets, DeFi , DEXs, stablecoins, cross-chain bridges, mixers, privacy-enhancing mechanisms, and other relevant technologies . Demonstrated ability to trace assets across multiple chains, protocols, and intermediaries and recognize when technical limitations prevent definitive continuity or attribution. Experience conducting transaction-graph analysis, wallet attribution , clustering, counterparty analysis, transaction-flow reconstruction, and investigative link analysis . Ability to critically assess blockchain attribution and distinguish among technical facts, commercial vendor intelligence, analytical inference, and unsupported assumptions . Experience integrating blockchain intelligence with off-chain evidence and enterprise information to develop investigative conclusions. Strong knowledge of fraud-investigation principles including corroboration, source evaluation, evidence preservation, timeline development, hypothesis testing, and documentation. Experience analyzing large or complex datasets and familiarity with tools such as SQL , advanced Excel, Python, Splunk, or comparable data-analysis technologies . Ability to clearly explain technically complex blockchain findings to audiences that may have little or no blockchain expertise. Strong investigative writing skills and demonstrated ability to produce accurate, concise, and defensible analytical products. Sound judgment and ability to work effectively where evidence is incomplete, conflicting, or evolving. Demonstrated discretion when handling sensitive employee, customer, investigative, security, or company information. Demonstrated experience mentoring, supervising, or reviewing the work of junior analysts or investigators. Nice to Haves Experience conducting blockchain investigations within a cryptocurrency exchange, blockchain analytics company, law-enforcement agency, regulatory organization, financial institution, intelligence function, or investigative consulting environment . Experience investigating digital-asset matters involving fraud proceeds, theft, account compromise, insider activity, social engineering, asset tracing, or complex cross-chain movement . Experience supporting asset recovery, law-enforcement referrals, subpoenas/legal process, civil litigation, regulatory inquiries, or other matters requiring defensible blockchain analysis . Experience investigating insider threats, employee misconduct, unauthorized access, data exfiltration, credential compromise, vendor fraud, conflicts of interest, or trusted-party abuse. Experience with OSINT, digital forensics, enterprise logs, security telemetry, or identity and access-management information . Experience creating custom blockchain analytics through APIs, SQL , Python, blockchain explorers, node data, or other raw-data sources , rather than relying exclusively on commercial graphical interfaces. Relevant blockchain-specific training or certifications, including certifications associated with Chainalysis , TRM Labs, or comparable blockchain-analysis platforms . Professional certifications such as CFE, CFCS, CAMS, GIAC, or comparable investigative, fraud , financial-crime, cybersecurity, or intelligence credentials . What Success Looks Like Success in this role requires significantly more than knowing how to enter an address into a blockchain analytics platform. The successful candidate should be able to receive a complex transaction, wallet, allegation, or investigative question and independently determine how to trace the activity, which chains and protocols are involved, what the available data establishes, what additional information is needed, what attribution can reasonably be made, and where the technical or evidentiary limitations prevent a definitive conclusion . The individual should be able to move seamlessly between on-chain and off-chain evidence , recognizing that a blockchain transaction may establish movement of assets without necessarily establishing the identity, knowledge, intent, or conduct of the person behind a wallet. They should also be capable of converting a highly technical blockchain investigation into a concise and defensible explanation that an investigator, attorney, executive, regulator, or law-enforcement partner can understand and act upon. At the same time, this person must be sufficiently versatile to apply the same investigative discipline to internal fraud , insider risk, enterprise data, third-party misconduct, and protective-intelligence matters when required. The hierarchy is much clearer this way: blockchain investigations are the specialized core competency; fraud /investigative intelligence is the broader mission; enterprise analytics and PST support are complementary capabilities. That should materially improve the candidate pool versus a title that makes blockchain expertise appear interchangeable with general data analytics. OKX Statement: OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. The salary range for this position is $143,000 - $214,000 The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Anthropic's Security Governance, Risk, and Compliance (GRC) team is the connective tissue that holds the company accountable to its security commitments. We translate regulatory, customer, and voluntary obligations into controls that teams act on, and give leadership a bird's-eye view of how well we're meeting them. We're building toward a fundamentally different kind of GRC: one that directs Claude, with the right humans in the loop, to challenge and evidence the performance of controls continuously rather than through periodic audits. Within Security GRC, Compliance & Audit Programs runs the integrated audit across our frameworks and maintains the Common Control Framework, the single set of controls that the whole program is built on. This role sits in Audit & Assurance and owns the framework and the assurance view across every control domain. About the role As part of the Security Audit & Controls team,  you will own the CCF across every control domain, from access and change management to logging, encryption, and people controls: which controls we have, what each one says, how each maps to the frameworks and commitments we hold, and whether each one is actually working. You'll work with control owners and GRC Partners to draft and validate control descriptions and activities that describe reality rather than policy intent, build the monitoring that shows operating effectiveness continuously instead of once a year, and drive what monitoring finds to closure with control owners. Building with Claude is a normal part of the job: drafting and mapping controls, testing evidence, and monitoring control health, with you deciding where human judgment stays in the loop. This is an individual contributor role for someone who works well independently, writes clearly, and gets satisfaction from a control set that is accurate, tested, and trusted by auditors and engineers alike. Key responsibilities Own the Common Control Framework: the canonical control set, its mappings to SOC 2, ISO 27001/42001, HIPAA, FedRAMP, and customer commitments, and the change process for adding, retiring, or rewording controls Draft and validate control descriptions and control activities with control owners, so each control states who does what, how often, in which system, and what evidence proves it Design and run continuous monitoring of control efficacy: define the metrics and automated tests that show operating effectiveness, tune out false positives, surface failures to owners before an auditor does, and build the controls maturity model that shows where each control domain stands and what it takes to move up a level Verify remediation and carry it into steady state: GRC Partners lead remediation in their domains and control owners implement the fixes. This role advises on control design and implementation, confirms fixes against what the auditor actually asked for, and keeps one source of truth for control and finding status. Once a fix holds, it works with the partner to standardize the evidence pull and, where appropriate, automate it or build continuous Map new frameworks and commitments onto the CCF as we commit to them, and support gap assessments when a new framework, certification, product, or entity comes into scope, using the CCF as the baseline and writing the requirements for each delta Support the integrated audit and customer audits: readiness checks, walkthrough preparation, evidence request lists, and the readout of external findings back to GRC Evaluate evidence reliability, including the completeness and accuracy of system-generated reports and AI-generated evidence, and set the standard for what audit-ready evidence looks like here Build with Claude: automate control mapping, evidence testing, and monitoring, and verify machine-drafted control language before it becomes the record Minimum qualifications Several years in IT audit, security compliance, or controls assurance, including hands-on ownership of a control framework or control library across more than one framework (for example SOC 2, ISO 27001, FedRAMP, HIPAA) Working command of audit mechanics: scoping, walkthroughs, sampling, design versus operating effectiveness, deficiency evaluation, and evidence reliability Experience writing control descriptions, control activities, and test procedures that other teams and external auditors relied on Experience with continuous controls monitoring or automated evidence collection, whether you built it, ran it, or audited it Enough technical fluency to read a runbook, a configuration, or a pipeline definition and judge whether it enforces what the written control claims Clear writing, because your control language and status reports are what auditors, engineers, and leadership work from Ability to get control owners and partner teams to prioritize and close work without having authority over them Preferred qualifications Have designed or rebuilt a common controls framework and led the remapping of existing frameworks onto it Have stood up continuous controls monitoring or automated evidence programs and can speak to coverage, false-positive rates, and what changed as a result Have applied LLMs to assurance work, such as control drafting, framework mapping, evidence testing, or monitoring Have defined or assessed controls for AI systems or agents operating in production, or for home-built internal systems Have provided requirements for a homegrown GRC platform and worked with the engineers who build it You don't need to Have done everything on this list. The scarce combination this role exists for is framework ownership plus the judgment to tell whether a control actually works Write production code. The bar is fluency sufficient to read, query, and challenge Hold every certification. CISA, CISSP, or similar are welcome and not required Have prior AI-industry experience Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas. However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers people to perform at a higher level through a deeper understanding of their bodies and daily lives. As a Senior Manufacturing Engineer, you will be responsible for developing manufacturing solutions that enable new products from early design through production ramp. You will work closely with Product Design, Mechanical, Electrical, Quality, and factory engineering teams to influence product design, define assembly strategies, and develop the fixtures, tooling, equipment, and processes required to manufacture products at scale. You will apply strong mechanical design fundamentals, DFX expertise, and hands-on manufacturing experience to identify manufacturing risks early, translate product requirements into robust manufacturing solutions, and solve complex technical challenges with a high degree of independence. RESPONSIBILITIES: - Partner closely with Product Design and Mechanical Engineering throughout product development to drive DFM, DFA, and DFX, identifying manufacturing risks and influencing product designs for assembly, quality, scalability, automation, and cost. - Develop manufacturing concepts and assembly strategies from early prototypes through production, translating product requirements into practical manufacturing processes, tooling, and equipment. - Design and develop fixtures, tooling, nests, gauges, and manufacturing aids used for assembly, alignment, bonding, welding, inspection, and test. - Own fixture and tooling development from concept through detailed design, tolerance analysis, fabrication, debugging, qualification, and release to production. - Apply GD&T, tolerance analysis, datum strategies, and mechanical design principles to ensure product and fixture designs support repeatable manufacturing and measurement. - Work with product engineering teams to evaluate component interfaces, assembly sequences, joining methods, tolerance stack-ups, and other design characteristics that impact manufacturability. - Develop and qualify manufacturing processes including adhesive bonding, heat staking, mechanical assembly, and other processes used in small consumer electronic devices. - Define critical process parameters, process windows, acceptance criteria, and controls to ensure manufacturing processes consistently meet product requirements. - Evaluate manual and automated assembly approaches and develop fixture and equipment concepts that enable appropriate levels of automation. - Use DOEs, process characterization, capability analysis, and failure analysis to validate manufacturing designs and optimize process performance. - Troubleshoot complex product, fixture, and process interactions during development builds and production ramp, driving issues to root cause and implementing robust engineering solutions. - Collaborate directly with contract manufacturers, equipment vendors, and tooling suppliers to develop, review, debug, and qualify manufacturing solutions. - Provide hands-on technical support during prototype builds, engineering validation, process qualification, and production ramp. - Travel domestically and internationally up to 25% to support development builds, tooling and equipment qualification, and production ramp. QUALIFICATIONS: - Bachelor's degree in Mechanical Engineering, Manufacturing Engineering, or a related technical field. - 5+ years of manufacturing engineering experience supporting product development and moderate- to high-volume manufacturing. - Ability to operate independently in fast-paced product development and manufacturing environments with limited technical oversight. - Strong experience applying DFM, DFA, and DFX principles during product development, with demonstrated ability to influence product designs for manufacturing. - Strong proficiency in SolidWorks, including detailed mechanical design, assemblies, drawings, and fixture design best practices. - Strong knowledge of GD&T, datum structures, tolerance analysis, tolerance stack-ups, and dimensional inspection methods. - Experience developing and qualifying manufacturing processes for small electromechanical or battery-powered electronic products. - Experience with manufacturing technologies including adhesives, heat staking, injection-molded plastics, and automated and manual assembly. - Strong understanding of injection-molded plastic part design principles, tooling considerations, defect modes, and their interaction with downstream assembly processes. - Experience designing and executing DOEs, process characterization studies, capability analyses, and structured failure investigations. - Strong hands-on mechanical/electrical and analytical problem-solving skills with the ability to independently develop solutions to complex product and manufacturing challenges. - Experience working directly with contract manufacturers, equipment vendors, tooling suppliers, and cross-functional product development teams. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.   The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The U.S. base salary range for this full-time position is $150,000 - $195,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.   In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.   These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing quickly. Key responsibilities Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention Design resource management and autoscaling so that compute follows demand as a run's needs shift Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems in production Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally Strong written communication, including design documents and incident writeups Preferred qualifications Experience running ML training or inference infrastructure at scale Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration Experience building schedulers, autoscalers, or resource management systems Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience with high-performance networking, RDMA, or collective communication libraries Experience building observability or automated remediation for large fleets Experience with async Python frameworks such as Trio or asyncio Familiarity with reinforcement learning or large language model training workloads Representative projects Design a scheduler that places training, sampling, and environment work across a heterogeneous cluster while respecting network topology and failure domains Build a failure detection and recovery system that lets a long-running job survive host and network failures with minimal lost work Scale environment execution substantially without increasing tail latency for the training step Design an autoscaling policy that rebalances compute across components as a run's bottleneck shifts Build a diagnostics system that explains why a run's throughput dropped and proposes a fix Trace a rare data corruption bug across many services to a race condition in a recovery path, and redesign the path so the class of bug can't recur Design the operational interface for a run so that automated tools can safely diagnose and adjust it under human oversight The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Chicago DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. About the Role We're looking for an AI Inference Platform Engineer to build, operate , and optimize the systems that serve large language , vision, multimodal, and embedding models across DRW. This role provides DRW's firmwide interface to modern AI models, from early evaluation through reliable production use . You'll work across inference runtimes, distributed systems, and production platform engineering, with deep GPU literacy.  You'll own the serving platform end-to-end: onboarding newly released models, measuring quality and performance equivalence across serving configurations, scheduling workloads across tenants, and continuously improving latency, throughput, utilization, reliability, and cost across the inference fleet. What You'll Do Optimize LLM inference performance across modern NVIDIA GPU architectures and inference runtimes. Build end-to-end performance profiling and observability to identify bottlenecks from individual GPU kernels through multi-node inference systems. Design and optimize KV cache and distributed inference architectures, including caching, routing, memory tiering, and prefill/decode strategies. Own day-0 model onboarding, determining the appropriate runtime, precision, sharding, memory, batching, cache policy, and serving configuration for new models. Maintain validated performance profiles for important model and hardware combinations, including performance and quality regression testing. Measure and monitor quality equivalence across serving configurations, including KV cache quantization, speculative decoding acceptance thresholds, precision choices, and model routing, so in-house serving can be trusted to match reference-model quality on production workloads. Manage the production serving lifecycle of models, including versioning, compatibility, staging, canarying, promotion, rollback, and retirement. Partner with SRE and platform teams to automate model deployment, distribution, production readiness, observability, and reliable operation across environments. Optimize model placement, scaling, and resource allocation across the inference fleet to improve utilization and cost efficiency while meeting performance and reliability requirements. Design and operate multi-tenant scheduling and isolation across shared GPU capacity, balancing latency SLOs, throughput, and priority across concurrent workloads. What We're Looking For The Tech Hands-on experience serving LLMs on NVIDIA GPUs, with familiarity across current and emerging architectures (Hopper, Blackwell, and successors), HBM, Tensor Cores, NVLink / NVSwitch , and the compute and memory bottlenecks that shape serving decisions . Deep expertise in at least one modern inference runtime such as TensorRT-LLM, vLLM, or SGLang. Practical knowledge of inference optimization techniques including continuous batching, scheduling, chunked prefill, speculative decoding, quantization, CUDA Graphs, and paged attention. Understanding of KV cache architecture, including prefix caching, block management, sizing, eviction, quantization, cache-aware routing, and multi-tier caching. Experience measuring model quality equivalence across serving configurations, including evaluation harnesses, task-specific benchmarks, and regression detection for quantization, KV cache, and speculative decoding changes. Experience designing and tuning distributed inference systems, including tensor parallelism, multi-node deployments, and disaggregated prefill and decode. Experience with multi-tenant GPU scheduling, workload isolation, and QoS across concurrent inference workloads. Proficiency with GPU performance and observability tooling such as Nsight, DCGM, OpenTelemetry, Prometheus, and Grafana. Strong Linux and systems performance fundamentals, with the ability to diagnose bottlenecks across hardware, drivers, runtimes, networking, and application layers. Production experience with model serving infrastructure, including CI/CD, automated testing, observability, and production readiness. The Intangibles You take a measurement-driven approach to performance optimization. You take ownership of performance problems across hardware, runtime, model, and infrastructure boundaries. You can move quickly and reprioritize as trading needs change, while maintaining a high bar for production systems. You understand the importance of reliability, predictability, and performance when AI systems are integrated into trading workflows and decision-making processes. You can evaluate unfamiliar models, runtimes, and hardware quickly and make sound engineering decisions with limited prior guidance. You communicate clearly and can explain complex performance tradeoffs across engineering teams. The annual base salary range for this position is $200,000 to $250,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . [#LI-VD1]

Location: San Francisco, CA Senior Software Design Lead, IDEO San Francisco In a nutshell: IDEO San Francisco is in search of a Senior Software Design Lead who will architect the human and technical systems behind the digital products and AI experiences we design, build prototypes that behave like real production software, and be the technical voice client CTOs trust. You'll pick up design at IDEO along the way. Why is this role important for IDEO’s work? Software design makes the biggest impact by turning a product vision into something a client can actually build, and by testing ideas in working code rather than static screens. Their skillset is critical to our business because the work has evolved from designing interfaces to designing systems: how people, software, and AI agents behave together. We count on them to understand data models, APIs and agentic infrastructure from first principles, and speak credibly on technical choices with executives and engineering leaders. Once here you will: Work with product designers, product strategists and design researchers on 8–12+ week digital product engagements that may span from product vision and strategy to full end-to-end build. You will play a key role in turning human insights into technical architecture: data, APIs, integrations and the agentic layer. Build early prototypes with real data, real models and real integrations, so we learn quickly and lower the risk of big bets. Advise client executives and engineering teams on tech stack choices, build-vs-buy, evaluating APIs and LLMs, and feasibility. Design how agents and systems behave on a human's behalf, including guardrails, failure states and how the system stays legible to both people and machines. Raise the craft bar inside IDEO. Create reusable starter kits and toolkits so teams stop building from scratch, and coach designers who prototype in code. Help shape proposals and scope technical work in business development. What does IDEO offer you? IDEO is a place where you can solve diverse, complex challenges for our clients and their organizations, alongside thoughtful, intelligent individuals who lead with curiosity, empathy, and humility. We intentionally craft moments that allow our community to pause, create, and connect. We encourage our community to bring their whole selves to work, respect the need for work-life balance, and allow for autonomy in the design process and your career. As a Software Designer in San Francisco, we provide the opportunity for you to: Learn design from a leading design and innovation firm . IDEO's founders designed Apple's first mouse and the first laptop. Since then, we've kept people at the center of design through every wave of technological change. You'd learn to do field research with real people, synthesize insights and tell compelling stories, and work alongside some of the best designers in the world. Work across many problem spaces . In one year you might redesign a retail or finance app, prototype new ideas in media and entertainment, and take on systemic challenges in health and education. Working across clients and industries stretches your thinking. A good solution isn't only technically sound: it has to fit real people, real businesses and the constraints they work within. Be in the room for the "why" before the "how." You'd shape the question from day one instead of receiving a spec after decisions have been made. And you’d help build this practice at IDEO to shape how next generation digital products are designed and built in the era of AI. Some previous projects to check out: Straight Arrow News : a redesigned news app and website with features like See All Sides, Sources and Media Landscape views. App page views grew 1,170% and active users 700%. This role would design the content and data model underneath and prototype with real feeds. Gates Foundation – Last Mile Money : human-centered design for 100+ digital financial products serving 34M underserved users. This role would work on architecture for low-connectivity settings and evaluate partner platforms and APIs. Jack Technology – Aitu : AI-enabled industrial sewing machines and a humanoid robot, designed around how they work with factory workers. This role would work on system behavior: how the AI signals what it's doing and how humans stay in control. Relevant experience and mindset: Must-haves: 6-8+ years as a software engineer shipping production software, ideally at growth-stage or established tech companies where speed and scale both mattered. You've taken products from concept to launch. 1-2+ years as an engineering lead or solutions architect: scoping, estimating and planning projects, and making architecture decisions others build on. You think at a systems level. Deep software fundamentals, including systems design, data modeling, APIs, and tradeoffs around performance, security and scale, plus fluency in a modern stack (e.g., TypeScript, React, Python, Node; AWS, GCP, Azure). Hands-on building with LLMs (tool use, agents, retrieval, evals) and advanced prototyping. You turn concepts into working software quickly, using real data and integrations, with quality that holds up beyond vibe coding. A track record of working closely with product, design and data, plus curiosity about people and a desire to learn how the craft of software intersects with product and design. You use prototypes as a way to think, not just to deliver. Strong communication and storytelling: architecture diagrams, system maps and presentations that make technical recommendations clear and persuasive to executives and engineering leaders. Nice-to-haves: Comfort with Figma, design systems and front-end craft Client-facing or consulting experience, or taking part in UX research Experience with hardware or connected devices (Arduino, IoT) Pop quiz, Hot Shot: A client's CEO wants "an AI agent in the app by Q2." What's your first question for the CEO? What's a piece of software that's beautifully built under the hood, not just on the surface? What makes it good? Application requirements and instructions: Résumé, LinkedIn + Cover Letter (Optional) GitHub or two to three work samples (code, architecture docs, side projects or technical writing) A short response of about 300 words: "Tell us about a technical decision you made that shaped how people experienced a product. What were the tradeoffs, and what would you do differently today?” Payscale & Benefits IDEO is committed to paying its employees, contractors & vendors equitably, regardless of gender identity or race/ethnicity/cultural identity. The salary range for this role is $130,000-150,000 USD. Final offers may vary based on candidate experience, location, and other factors. As a full-time position, this role is eligible for employee benefits. In addition to base compensation, IDEO offers a rich benefits package including the following: Hybrid Model: Team members based in the San Francisco Bay Area are expected to work in the studio on Tuesdays, Wednesdays, and Thursdays, with flexibility based on client travel, project needs, and deliverables. Candidates based outside the Bay Area are not expected to be in the studio regularly, but should be available to travel as needed for IDEO and client work. Health Benefits: Vision, Dental, Healthcare Financial Benefits: 401K with Employer Contribution Family & Caregiving: Parental Leave, Adoption Assistance, Fertility Assistance, Transgender Medical Assistance, Breastmilk shipment, Back-up/Dependent Care, Pet Insurance Other Benefits: Flexible Work, Flexible Time Off, Paid Holidays, Annual Education Stipend, Home Office Stipend, Commuter Reimbursement, and Phone & Internet Reimbursement Commitment to Diversity At IDEO, we are committed to the work of advancing diversity, equity and inclusion within our organization and in the world. Our purpose of having disproportionate, world-changing impact through design is directly connected to our ability to bring many different perspectives to the table. This applies to our candidates, the people we hire, the clients and customers we serve, and the communities we learn from in our research. Please note that the successful candidate must be based in the United States and have the unrestricted right to work in the US. Unfortunately, we are unable to offer sponsorship for this role. IDEO proudly supports flexible work.

Задачи: — Manual testing of features, bug fixes, and releases throughout the development process — Write, review, and execute test cases — Identify, document, and track bugs — Collaborate with developers and team members to resolve issues — Perform regression and post-release testing — Ensure product quality and consistency with requirements — Use AI tools (e.g., ChatGPT) to assist with testing tasks, writing test cases, and analyzing issues Требования: — Basic practical experience in QA (courses, pet-projects, or commercial) — Understanding of QA fundamentals (test cases, bug lifecycle, etc.) — Strong attention to detail and analytical thinking — English level B2 or higher (reading & writing) — Ability to work independently and in a team Плюсы: — Experience with Shopify — Familiarity with Agile/Scrum — Experience with bug tracking systems (JIRA or similar) Инструменты: — JIRA — Confluence — Google Workspace — Slack — Shopify Условия: — Fully remote, full-time (40h/week, flexible schedule) — Salary paid twice a month — 20 working days paid vacation — 10 paid sick leave days — Opportunities to grow in QA

Location: Remote US At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Fraud team at Affirm Bank works cross-functionally with Machine Learning, Product, Engineering, Operations to combat fraudulent activities to foster a safe platform. This role requires abundant cross-functional partnership. This individual will be the representative of the Credit Risk org, leading the charge on refining our Identity Verification and Fraud processes as well as our Application flow. Additionally, this role will work closely with the Product and Engineering teams to improve our Fraud solution. Come join us in our mission to change consumer finance through better technology, lower costs, and increased transparency while providing the best customer experience. What You'll Do This role will take charge of owning fraud performance for depository products, including monitoring fraud losses, approval rates, false positives, customer friction, and other key risk metrics Data Pipeline, Analytics & Monitoring Build and maintain scalable data models and transformation pipelines, using tools (such as DBT) to standardize depository product, transaction, customer, fraud, and operational data. Define trusted fraud performance metrics and analytical datasets, including fraud loss rates, approval and decline rates, false-positive rates, customer friction, and operational efficiency. Develop recurring dashboards, scorecards, and monitoring frameworks to provide clear visibility into fraud performance, portfolio health, and emerging risks. Conduct deep-dive analyses to diagnose fraud losses, control gaps, false positives, portfolio shifts, and unexpected performance changes, translating findings into actionable recommendations. Fraud Strategy Building & Optimization Develop and optimize fraud rules, policies, thresholds, models, and decision strategies that balance loss prevention, customer experience, operational capacity, and product growth. Evaluate new data sources and signals to improve detection of identity risk, account takeover, device risk, transaction risk, and other fraud typologies relevant to depository products. Lead testing and performance measurement of fraud strategy changes, including rule launches, model updates, policy changes, and new product controls, with clear pre- and post-implementation evaluation. Partner cross-functionally with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk to improve fraud strategies, strengthen operational feedback loops, and support new product launches. What We Look For EXPERIENCE - 7+ years’ of Analytics experience PRODUCT KNOWLEDGE - Passion to understand how Affirm product works and a curious mindset to help change and make it more effective TECHNICAL SKILLS - Fluent in SQL and Python PEOPLE SKILLS - A team player with ability to collaborate and influence across many different teams in the organization COMMUNICATION - Ability to communicate findings and recommendations clearly to both technical and non-technical audiences EXECUTION - Able to thrive in a fast-paced environment and be responsive and available during times of peak fraud activity MULTI-TASKING - Strong time management skills and the ability to manage multiple projects and priorities RISK KNOWLEDGE  - Working knowledge of the fundamentals of payment processing and an understanding of industry risk trends, including familiarity with fraud strategy development We also encourage you to read our Chief Risk Officer’s views on what makes Credit Risk Managers influential and on a Modern Risk Management System . Base Pay Grade - M Equity Grade -  USA 8 Employees new to Affirm typically come in at the start of the pay range . Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA base pay range (CA, WA, NY, NJ, CT): $185,000 - $245,000 USA base pay range (all other U.S. states): $164,000 - $224,000 Please note that visa sponsorship is not available for this position. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking an experienced public opinion researcher to build and expand Anthropic's in-house polling and research function. This role will be fundamental to understanding how key audiences — from policymakers and third-party groups to the general public — perceive and respond to Anthropic's policy positions, messages, and campaigns. This is a foundational role: you'll establish the research function from the ground up, with high autonomy and limited precedent. The Central Policy team sits at the operational heart of Anthropic's policy function — distinct from government relations and communications, but essential to enabling both. You'll work cross-functionally to ensure our policy and communications strategy is grounded in a rigorous understanding of stakeholder sentiment. The polling insights you generate will directly feed into high-visibility campaigns and will be a key asset in our policy efforts in Washington and beyond. Anthropic is equal parts research lab, policy think-tank, and technology startup. We care deeply about the safe development of AI systems and build partnerships with governments through proactive, opinionated, substantive policy conversations. This role offers a unique opportunity to be at the forefront of AI policy, bringing rigorous research discipline to policy strategy. Success in this role means establishing trusted relationships with leading polling firms around the world, delivering high-quality research on a regular cadence, and becoming the internal expert on how key audiences perceive AI, Anthropic, and Anthropic's positions and messages. You'll translate polling insights into strategic recommendations that measurably improve campaign effectiveness, and build scalable processes that allow the function to grow efficiently as demand increases. Key responsibilities Develop a comprehensive strategy for our in-house political research function that aligns with Anthropic's policy goals Identify, evaluate, and establish relationships with leading research and polling firms, ensuring coverage across demographics, geographies, and political perspectives Conduct detailed, proactive research to test core messages, policy proposals, and campaign themes, and to evaluate Anthropic's brand perception and performance Execute rapid-response polling to quickly assess Anthropic's messaging strategy in response to external events, policymaker actions, competitive developments, or emerging opportunities Work with external affairs colleagues (federal, state, and international) and policy communications to identify research priorities, interpret findings, and translate insights into actionable strategic recommendations Develop and maintain a knowledge management system for polling data, insights, and recommendations that ensures findings are accessible and actionable Manage polling vendors at scale, including vendor performance management Participate in strategy sessions and provide thought partnership on the design of messages, policy proposals, and campaigns ahead of polling and testing Create clear, compelling deliverables that distill polling findings into insights and recommendations Identify opportunities to build and scale the polling function over time, including staffing needs, process improvements, and capability expansion Track and report on the impact and utility of research, measuring how insights translate into more effective campaigns and strategic decisions Minimum qualifications Experience designing and executing public opinion research, including survey and questionnaire design, sampling approaches, and message testing Ability to analyze quantitative and qualitative polling data and translate findings into clear, decision-ready written recommendations Experience selecting, briefing, and managing external polling or research vendors Strong writing and presentation skills, including distilling complex research for senior, non-technical audiences Preferred qualifications 8+ years of professional experience in political or public opinion research, ideally spanning multiple campaign cycles and policy environments Corporate public affairs experience, ideally in a highly scrutinized or regulated industry Strategic thinking that spots emergent issues, identifies and tests the right messages, and translates those insights into tactical recommendations A track record of building relationships with vendors, external experts, and complex stakeholder ecosystems Strong organizational skills, with the ability to manage multiple projects simultaneously, maintain clear priorities, and deliver on tight timelines Comfort operating in ambiguous environments, taking ownership of problems, and proactively driving initiatives with limited precedent A resourceful, collaborative working style and genuine commitment to being a strong teammate Passion for AI policy and alignment with Anthropic's safety mission and commitment to responsible AI development The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $230,000 — $265,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: United States (Remote); Seattle, Washington; San Francisco, California Workplace: Remote ROLE SUMMARY Temporal is looking for a Software Engineer II to join the Open Source Server team. This team builds and maintains the core Temporal server. Its scope is broad, including Matching, Applications, Foundations, task processing, quotas and throttling, visibility, developer-facing primitives such as standalone activities, schedules, and streaming, and workflow experience improvements such as Continue-As-New, pause, and reset. We do not expect one person to cover all of these areas. We’re looking for an engineer who is excited to learn the system, contribute to new and/or ambiguous projects across the codebase, and help improve the reliability, performance, operability, and developer experience of Temporal over time. This is a hands-on engineering role where you’ll collaborate with experienced engineers to design, build, and operate components of Temporal’s distributed systems platform while growing your skills in distributed systems engineering. WHAT YOU'LL DO • Design, implement, test, and ship well-scoped features and improvements for the Temporal server with support from teammates. • Work on distributed systems problems in areas such as task matching, scheduling, workflow execution, visibility, quotas, throttling, persistence, developer primitives, and workflow lifecycle features. • Make thoughtful engineering tradeoffs with guidance, balancing developer experience, performance, and operability requirements. • Partner with engineers, product managers, cloud teams, and customer-facing teams to understand requirements and deliver scalable solutions. • Improve the reliability and operability of the server by adding tests, instrumentation, dashboards, alerts, runbooks, and documentation. • Participate in design discussions and code reviews to learn best practices and contribute to a high-quality codebase. • Contribute to improving the developer experience for open source users and enterprise customers through incremental improvements and bug fixes. • Share knowledge with teammates and contribute to a collaborative engineering culture. WHAT YOU'LL BRING • Experience building and operating production backend systems (distributed systems experience and concurrency experience). • Strong computer science fundamentals, including concurrency basics, data structures, and debugging. • Experience writing production-quality code in Go, Java, or another applicable backend language, with an emphasis on correctness and maintainability. • Familiarity with core distributed systems concepts (e.g., fault tolerance, consistency tradeoffs, replication, scheduling, performance), with interest in deepening these skills. • Ability to break down ambiguous problems into smaller tasks, ask good questions, and incorporate feedback from code review. • Comfort working collaboratively across teams and communicating progress, risks, and tradeoffs clearly. • Experience with testing practices and an operational mindset (logging, metrics, tracing, on-call empathy) is a plus. • Experience with open source software or communities is a plus. • Experience with AWS, Azure, or GCP is a plus. • Exposure to technologies such as Elasticsearch, OpenSearch, ClickHouse, Cassandra, PostgreSQL, or MySQL is a plus. • Exposure to Kubernetes or related tooling (CRDs, KEDA, Argo) is a plus. WHAT MAKES YOU A GOOD FIT • You’re excited to continue building and deepening your distributed systems expertise. • You enjoy learning large, complex codebases, think critically, thrive in ambiguity, and enjoy solving challenging problems. • You take ownership of your work, follow through, and collaborate well with teammates. • You balance technical depth with practical engineering decisions and are comfortable iterating toward better solutions. • You don’t need prior Temporal experience—you’re excited to work on the core of a distributed system used by a large open source community and enterprise customers. Temporal Technologies is an Equal Opportunity Employer. Temporal Technologies does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. We embrace and celebrate differences and diversity. Temporal is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. If you need to request a reasonable accommodation, please let your Recruiter know so we can assist.

Location: Russia; Perm; Moscow Workplace: remote ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. THE ROLE We are hiring a Team Lead, Web3 to lead a cross-functional team of frontend, backend, smart contract and QA engineers in XsollaZK, Xsolla's Web3 ecosystem on a zkSync-based L2. Your team builds: smart wallets built on account abstraction; SDKs that game studios and partners use to bring players on-chain; infrastructure backend services for tokenizing in-game items and currencies; ecosystem dApps: a DEX, an NFT marketplace and an auction. This is a management role. Most of your time goes to people and delivery: building the team, growing engineers, and making delivery predictable. The rest goes to technical leadership: architecture, reviews and hands-on code where it matters. Responsibilities WHAT YOU WILL OWN The team: hiring, onboarding, growth and performance of frontend, backend, smart contract and QA engineers Delivery: predictable commitments, a sustainable pace and the quality of what the team ships How the team works: processes, engineering standards and an AI-assisted workflow Relationships with Product, DevOps and other Xsolla product teams: priorities, dependencies and expectations The technical direction of the team's product area: on-chain / off-chain architecture and key technical decisions, justified in writing Security and reliability of what the team ships: signing flows, contracts that hold user assets, production operation and the team's on-call rotation WHAT YOU WILL DO People Set clear goals and expectations for each engineer Run regular 1:1s, performance reviews and career development conversations; give direct feedback and address underperformance Hire engineers across disciplines: define roles, run interviews and onboard new people Grow engineers through mentoring and build the team's next leaders Build a culture of technical excellence, collaboration and continuous learning Delivery Work with Product to shape requirements, estimate and plan work Manage scope, workload, risks and dependencies so the team delivers on its commitments Report progress, risks and blockers to stakeholders Lead the team through production incidents and post-mortems Continuously improve development processes and team efficiency Technical leadership Review architecture and critical code across backend, frontend and smart contracts, with a focus on edge cases specific to Xsolla products: smart wallets, tokenization of in-game items and currencies, marketplace and auction flows Lead key decisions on smart wallet integration (UserOperations, paymaster and gas sponsorship), session keys and the signing flow Identify systemic risks (key management, signature phishing, bundler and RPC dependencies) and make sure they are addressed before they become incidents Contribute hands-on to critical features when needed Set up AI tooling in the repositories (Claude Code, Codex, Cursor: rules, context, harness) and drive its adoption across the team REQUIRED Management experience 5+ years of engineering management experience Managing cross-functional teams that combine several disciplines (for example frontend, backend, smart contracts and QA) Teams you led shipped dApps to production and maintained them People leadership Hiring and building teams: defining roles, running interviews, onboarding Performance management: setting goals, giving feedback, running performance reviews, handling underperformance Growing engineers: career plans, mentoring Delivery and stakeholders Delivery planning: estimation, sprint planning, managing scope, risks and dependencies Working with Product and other teams on priorities and trade-offs; explaining technical trade-offs to non-technical stakeholders Leading a team through production incidents and post-mortems Balancing management with hands-on technical work Technical depth A strong technical background: hands-on engineering experience across the Web3 stack, deep enough to lead technical decisions and review work on each layer: Web3 libraries and wallets: viem and wagmi in production; how wallet signers work (EOAs, browser and embedded wallets, smart accounts, EIP-191, EIP-712, EIP-1193); smart wallets (UserOperations, paymasters, ERC-1271) Backend: Go and TypeScript (Node.js); processing on-chain events (idempotency, reorgs, retries); asynchronous messaging (Kafka, RabbitMQ or NATS ); PostgreSQL and Redis; REST and gRPC API design Frontend: React and TypeScript; web security fundamentals ( XSS , CSRF , CSP , safe handling of signatures and keys in the browser) Smart contracts: reading Solidity and the EVM (storage, gas, proxy upgrade patterns, access control); common vulnerability classes (reentrancy, front-running / MEV , oracle manipulation, signature replay) Operations: Docker, Kubernetes, CI/CD; observability (we use Datadog; experience with Prometheus, Grafana, ELK / Graylog or OpenTelemetry also counts) AI-assisted engineering Daily hands-on use of AI coding tools (Claude Code, Codex, Cursor) for development and review, including configuring them for a repository English Spoken English at B2 level or higher Nice to Have ZK Stack and zk -rollups: EraVM vs EVM , system contracts (ContractDeployer, NonceHolder), L1↔L2 messaging, bridging and finality Smart contract development in Solidity with Foundry Deeper account abstraction: ERC-4337 EntryPoint versions and validation rules (ERC-7562, ERC-6492), modular accounts (ERC-7579 / ERC-6900), session keys and delegated permissions (ERC-7710 / ERC-7715), EIP-7702 Hands-on experience with wallet and AA infrastructure technologies (Sequence, thirdweb, Privy, Dynamic, Turnkey, Pimlico, Alchemy, ZeroDev, Safe{Core}), with clear views on build versus buy Key management: HSM , MPC / threshold signing, social or guardian-based recovery DeFi ( DEX , AMM ) and NFT marketplaces (ERC-721, ERC-1155, auctions) go-ethereum and abigen Managing distributed or remote teams Gaming or fintech experience with high-load systems HOW WE WORK Decisions in writing. Significant technical decisions are written up as an RFC or ADR that lays out the options and trade-offs. We discuss the document, not a blank whiteboard. AI is part of everyday engineering. We use AI coding tools for development and review, and we treat configuring them for a codebase as real engineering work. HOW WE HIRE Intro call. Your background, your motivation and the role. Technical interview. Built on the Technical depth part of the Required section and the technical items in What you will own . People and delivery. Built on the Management experience , People leadership and Delivery and stakeholders parts of Required : real situations from your experience with hiring, performance, delivery and incidents. Bar raiser. An engineer from outside the hiring team checks that you raise the overall engineering bar. BENEFITS We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we're not just building a business; we're cultivating a community that values creativity, collaboration, and the transformative power of play. EMPLOYMENT DETAILS Location: Remote  Employment Type: Full-time Schedule: 10:00–19:00 (flexible) Contract: Employment agreement (entity or EOR arranged per candidate location) EQUAL EMPLOYMENT STATEMENT Xsolla is dedicated to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, language, sexual orientation, national origin, genetics, political beliefs, disability, age, marital status, social background or other characteristics. We are committed to compliance with all fair employment practices regarding citizenship and immigration status. CONTACT If you have questions regarding our hiring practices, please contact careers@xsolla.com. For more vacancies, visit xsolla.com/careers.

Location: Israel; Portugal; Poland Workplace: remote About airSlate airSlate is a global SaaS technology company that develops no-code workflow automation, electronic signature, and document management solutions. Our award-winning products - SignNow, pdfFiller, DocHub, altaFlow, Instapage, and US Legal Forms - serve over hundreds of millions of users and more than one million customers worldwide, helping organizations of every size digitize processes, improve efficiency, and transform how they work.   We’re in an exciting phase of growth and transformation, with teammates in more than 20 countries across three continents and main hubs in the United States, Poland, Ukraine and Philippines.  At airSlate, we’re building value for customers and a culture where growth and innovation go hand in hand. We’re looking for people eager to shape products, scale a company, and thrive in a fast-moving environment. About SignNow team: We are a passionate and ambitious team of 140+ people on a mission to succeed with our award-winning signature solution – SignNow. SignNow empowers over 28 million people at companies across the world to move fast with everything they need to send and eSign their documents. Increase productivity with document workflows, impress customers, and save money while maximizing ROI with SignNow. And now, we are looking for a Senior Content Manager who is prepared to contribute to the next chapter of our company's growth. The person will join the SignNow Product Marketing team and take on the responsibility of creating and managing content across the funnel, including the website, blog, email, sales collateral, and social, to support product launches, GTM campaigns, and sales enablement. As Senior Content Manager, you will own content end to end, from brief to production, publishing, and optimization, working closely with the Principal Product Marketing Manager with direct line of sight into product strategy and launches. What you'll be working on: Create and execute content strategy: decide what we do, why, and what result we expect Own content across its full lifecycle: brief, production, publishing, optimization, and performance review Partner with Product Marketing, Design, Sales, and Customer Success to deliver content for product launches, GTM campaigns, and sales enablement Optimize content based on performance data such as organic traffic, engagement, CTA conversion, and search visibility Keep messaging consistent across all channels and formats, and fix drift when it appears Use analytics tools such as GA4 and Ahrefs to understand what works, what doesn't, and why, and act on the findings Evaluate and adopt new content technologies and platforms that improve quality or speed Use AI writing tools (e.g., ChatGPT, Claude) as a deliberate part of your workflow for ideation, drafting, and iteration, applying editorial judgment to every output What we expect from you: Proven experience creating content across multiple formats and channels, with a portfolio that shows range and quality Experience in a B2B SaaS environment A solid grasp of SEO fundamentals and conversion-focused writing An understanding of marketing fundamentals, including funnel stages and how content serves each one Technical comfort with CMS platforms and publishing and collaboration tools Structured, integrated use of AI writing tools in your content workflow Excellent English What helps you rock: B2B SaaS experience where your content contributed directly to pipeline, trial activation, or product adoption Experience working with Product Marketing or Product teams on launch content or feature messaging A product marketing background or training A track record of turning content performance data into strategic decisions What we offer   Flexible working environment - Our teams operate across the globe. We value in‑person collaboration in our hubs, but we also embrace remote and hybrid working. You can work from one of our offices in the United States, Poland, Romania or Ukraine, or remotely from many countries.   Competitive compensation and stock options - We offer salaries that reflect local market conditions and experience,  plus a performance-based bonus system and stock options so you share in the company’s growth.   Professional growth and learning - We invest in your development through courses, conferences, and access to learning resources. We encourage career growth and internal mobility, supporting teammates who want to explore new opportunities within airSlate.   Health and well‑being - We provide comprehensive benefits tailored to each country, including health coverage, wellness programmes and access to fitness options. We also dedicate quarterly company-wide Mental Health Days, when everyone takes time off to rest and recharge.   Family‑friendly culture - Family life is part of who we are, and we embrace it in many forms. From flexibility for parents to our airSlate Junior Club for kids, to company-wide family days and our pet-friendly approach, we’re committed to making work and life easier to balance.   Giving back - We support charitable initiatives around the world through the airSlate Care programme. Our current focus includes humanitarian aid in Ukraine and other regions, matching employee donations and supporting causes chosen by our teams.   Open communication - We encourage transparent dialogue at all levels. From team discussions to company-wide Q&A sessions with our CEO, we make sure everyone has the chance to be heard and to influence how we grow.       It is airSlate's policy to comply with all applicable equal employment opportunity laws by making all employment decisions without unlawful regard or consideration of any individual’s race, religion, ethnicity, color, sex, sexual orientation, gender identity or expressions, transgender status, sexual and other reproductive health decisions, marital status, age, national origin, genetic information, ancestry, citizenship, physical or mental disability, veteran or family status or any other basis protected by applicable national, federal, state, provincial or local law. airSlate's policy prohibits unlawful discrimination based on any of these impermissible bases, as well as any bases or grounds protected by applicable law in each jurisdiction. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. airSlate is pleased to provide such assistance and no applicant will be penalized as a result of such a request. Pursuant to relevant law, where applicable, airSlate will consider for employment qualified applicants with arrest and conviction records.   Read our Recruitment Privacy Notice to Learn how we process your personal information.

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building high-load products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. We are looking for a Lead ML Engineer to own a new ML stream focused on fast delivery of applied machine learning solutions across different product and business domains. The stream will work with a broad range of ML challenges. Some initiatives may be relatively small and delivered within a few weeks, while others may prove their value and grow into larger dedicated projects. This role combines hands-on ML engineering with end-to-end technical delivery ownership. You will receive product problems and expected outcomes from Product or internal stakeholders, clarify the technical requirements and constraints, define the implementation approach, coordinate execution within the stream, and bring solutions to production readiness and launch. This is a highly hands-on role. The stream will not have a dedicated software engineer for every initiative, so we expect Data Scientists and ML Engineers to be comfortable working beyond experimentation and contributing directly to production code. The role is not tied to a single ML domain. We value strong ML fundamentals, engineering skills, pragmatism, and the ability to quickly understand new problem areas more than deep specialization in one particular class of models. Job Responsibilities Technical Delivery Ownership Turn product and business problems into concrete ML implementation plans. Clarify requirements, constraints, available data, integrations, and success criteria together with Product and relevant stakeholders. Define technical scope, milestones, dependencies, risks, and delivery estimates. Select appropriate ML approaches and determine the fastest reliable way to validate and implement them. Drive technical delivery through experimentation, implementation, integration, deployment, and launch readiness. Keep delivery on track, proactively identify blockers, and coordinate dependencies with other teams. Provide Product with clear technical options, trade-offs, estimates, risks, and experiment results required for product decisions. Support production rollout and iteration based on observed results. Hands-on ML & Engineering Design, train, evaluate, and deploy ML models across different domains and problem types. Write production-quality Python and contribute directly to implementation. Build APIs, batch jobs, data-processing pipelines, and ML services required to deliver solutions where appropriate. Work with classical ML, deep learning, and foundation-model-based approaches depending on the problem. Process and transform large production datasets using Python and SQL. Integrate models into existing production systems. Implement appropriate testing, monitoring, logging, and observability for delivered ML solutions. Work within the shared ML infrastructure, architecture, and engineering practices used across the company. Collaborate with Data Science, Backend, Data Engineering, and MLOps specialists when deeper domain expertise or infrastructure changes are required. Stream Execution Break initiatives down into concrete technical tasks and coordinate execution within the stream. Coordinate the work of Data Scientists and ML Engineers contributing to stream initiatives. Review technical approaches, experiments, and implementation. Keep the team focused on the agreed scope, priorities, and delivery timeline. Identify technical risks and dependencies early and drive them to resolution. Escalate architectural, infrastructure, or methodological questions when broader alignment is required. Help prepare successful initiatives for scaling or transition into longer-term ownership if they grow beyond the scope of the stream. Cross-functional Collaboration Work closely with Product throughout the delivery lifecycle. Independently gather the technical details and constraints required to execute on a product request. Communicate estimates, dependencies, technical trade-offs, and delivery status clearly. Work directly with Engineering and other internal teams to unblock implementation. Challenge technically unclear, contradictory, or infeasible requirements and propose practical alternatives. You’ll thrive here if you have 5+ years of commercial experience in Machine Learning, Data Science, or ML Engineering. Strong hands-on Python programming and software engineering skills. Experience taking ML solutions from a product requirement through experimentation, implementation, integration, and production. Strong understanding of machine learning methods, statistics, experimentation, and model evaluation. Experience writing maintainable production code rather than working exclusively in notebooks. Experience building APIs, services, batch processing, or data pipelines. Strong SQL skills and experience working with large production datasets. Practical experience with Docker and production deployment environments. Ability to turn partially defined problems into concrete technical plans. Ability to estimate work, identify dependencies and risks, and drive technical execution against a timeline. Experience owning technical delivery involving several contributors and coordinating work across dependencies. Experience reviewing code and technical approaches. Ability to work effectively within established engineering and ML practices while independently owning delivery within a stream. Strong communication skills and the ability to work directly with Product and technical stakeholders. Ability to balance speed and engineering quality: validate ideas quickly when uncertainty is high and build robust solutions when moving towards production. Nice to Have Previous experience as a Tech Lead, Stream Lead, or technical owner of ML initiatives. Experience with Kubernetes and CI/CD. Experience with Kafka or other streaming platforms. Experience with Airflow, MLflow, experiment tracking, model monitoring, or similar tooling. Experience building real-time or high-load ML services. Experience with FastAPI or similar Python service frameworks. Experience across several ML domains, such as recommendation systems, ranking, NLP/LLMs, Computer Vision, anomaly detection, forecasting, or classification. Experience with LLM inference, fine-tuning or other GenAI systems. Experience in teams where Data Scientists and ML Engineers own a substantial part of production implementation themselves.

Location: Remote, Україна; Україна We are looking for an UX/UI Designer to own and elevate the end-to-end user experience across OneDome’s core products, including: Customer-facing web and mobile journeys Transaction management platform The upcoming OneDome mobile app This is a hands-on senior role with real ownership. You will shape how customers and partners experience OneDome at scale. Responsibilities Product & UX Own end-to-end UX/UI for complex, multi-step financial and legal journeys Translate business requirements and user needs into intuitive, scalable designs Design flows that reduce friction, increase conversion, and improve completion rates Lead discovery, user journey mapping, wireframing, prototyping, and usability testing UI & Design Systems Create high-quality UI designs aligned with OneDome’s brand and product vision Evolve and maintain a scalable design system (components, patterns, accessibility) Ensure consistency across web, mobile, and internal platforms Collaboration Work closely with Product Managers, Engineers, Marketing, and Operations Partner with developers to ensure high-quality implementation Present design decisions clearly to senior stakeholders and leadership Optimization & Scale Use data, user feedback, and experimentation to continuously improve UX Design for scale: thousands of transactions, multiple user types, and growing feature sets Balance speed of delivery with design quality in a fast-moving environment What We’re Looking For Experience 3+ years experience in UX/UI or Product Design Strong experience designing complex, transactional or fintech products Proven experience owning large parts of a product end-to-end Skills Expert in Figma (or similar modern design tools) Strong UX fundamentals: user research, IA, interaction design, usability Strong visual/UI design skills with high attention to detail Experience working with design systems at scale Ability to simplify complex flows without losing compliance or accuracy Mindset Product-first thinker with strong commercial awareness Comfortable operating in a high-growth, fast-paced environment Pragmatic, execution-focused, and outcome-driven Confident working with senior stakeholders and challenging assumptions Nice to Have Experience with fintech, banking or regulated products Mobile app design experience (iOS / Android) Experience designing internal tools or B2B platforms Familiarity with accessibility standards (WCAG) Why Join OneDome Work on a genuinely category-defining product Huge ownership and visibility across the business Direct impact on millions of pounds of transactions Fast-growing, ambitious, high-performance culture Opportunity to shape the design foundation of a future superapp Salary: $3,000 – $4,000 / month