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Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a VP of Research (Machine Learning) to define and lead the research direction behind its AI platform. This leadership role will shape how AI systems reason, learn, evaluate, and continuously improve within a product designed for high-frequency, real-world usage. Working closely with product and engineering leadership, this position will drive the long-term intelligence strategy, balancing cutting-edge research with practical production impact. Key Responsibilities Define and evolve the research roadmap for the platform's core AI intelligence, including context representation, memory, reasoning, planning, and orchestration. Evaluate and determine when to develop proprietary model architectures versus leveraging or adapting frontier open-source and commercial AI models. Design evaluation frameworks that measure real-world performance, robustness, safety, and long-term system behavior beyond traditional benchmark metrics. Lead the company's AI alignment, safety, and guardrail strategy as a core component of product development. Drive research and experimentation across advanced machine learning techniques, including: Retrieval-Augmented Training (RAG) Mixture of Experts (MoE) Model Distillation Multi-Agent Orchestration Multimodal AI Systems Partner closely with product and engineering teams to define and execute the intelligence strategy for AI-powered applications. Establish and maintain high standards for research quality, technical judgment, and engineering excellence across the organization. Requirements Extensive experience designing, building, and deploying machine learning systems in production environments. Strong technical expertise in model behavior, failure analysis, system evaluation, and long-term AI performance. Proven ability to translate advanced research into reliable, production-ready AI solutions. Demonstrated experience making high-impact technical decisions in fast-moving and ambiguous environments. Deep understanding of AI evaluation methodologies, model robustness, safety, and system reliability. Strong ownership mindset with the ability to lead technical strategy and execution. Passion for building practical AI systems that deliver measurable real-world impact rather than focusing solely on academic research or benchmark performance. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Technical Lead, Machine Learning to lead the execution of its AI platform by translating research into scalable, production-ready machine learning systems. This role sits at the intersection of research, infrastructure, and product, with responsibility for ensuring models are trainable, deployable, observable, and optimized for real-world performance. Working closely with research, engineering, and product teams, this position will drive the development of robust ML infrastructure while balancing performance, reliability, latency, and cost. Key Responsibilities Lead the end-to-end execution of machine learning systems, including data pipelines, training workflows, evaluation frameworks, inference architecture, and production deployment. Fine-tune and optimize models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation . Design, build, and operate scalable inference systems with a focus on latency, cost efficiency, and reliability. Develop and maintain data pipelines for both synthetic and real-world training datasets. Build evaluation frameworks to measure model performance, robustness, safety, and bias in collaboration with research teams. Optimize production deployments through GPU utilization, memory efficiency, inference optimization, and scaling strategies. Partner closely with application engineering teams to integrate machine learning systems into backend, desktop, and mobile products. Continuously improve production systems through rapid iteration, monitoring, and data-driven optimization. Requirements Proven experience building and deploying production-grade machine learning systems used by real users. Strong expertise working with large language models and understanding model behavior, limitations, and failure modes. Experience developing scalable ML infrastructure, training pipelines, and inference systems. Strong software engineering skills with the ability to write maintainable, production-quality code. Experience balancing real-world production constraints, including latency, reliability, scalability, cost, and safety. Strong ownership mindset with the ability to independently drive technical initiatives from design through deployment. Excellent communication and collaboration skills, with experience working in cross-functional, high-performing engineering teams. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Senior Machine Learning Engineer to design and build production-grade machine learning systems that power its AI platform. This is a hands-on technical role focused on solving complex machine learning challenges, translating research into scalable solutions, and delivering reliable AI systems that operate effectively in real-world environments. Working closely with research, product, and engineering teams, this position will independently own critical machine learning components from development through production deployment. Key Responsibilities Build and develop core machine learning systems that power AI-driven product capabilities. Own the end-to-end machine learning lifecycle, including data preparation, model training, evaluation, inference, deployment, and continuous iteration. Translate research concepts into reliable, production-ready machine learning solutions. Investigate and resolve model performance issues and production system failures using real-world operational insights. Continuously improve machine learning systems through rapid experimentation, measurement, and iteration. Collaborate closely with research, product, and engineering teams to deliver impactful AI features. Provide technical guidance through code reviews, best practices, and mentorship of fellow machine learning engineers. Develop solutions that balance real-world production requirements, including latency, scalability, cost efficiency, reliability, and safety. Requirements Proven experience building and deploying production machine learning systems used by real users. Strong understanding of modern machine learning models, including their behavior, limitations, and failure modes in production environments. Excellent software engineering skills with the ability to develop robust, maintainable, production-quality systems. Experience designing and implementing scalable machine learning pipelines and infrastructure. Strong ownership mindset with the ability to independently solve complex technical challenges from concept through deployment. Excellent problem-solving, communication, and collaboration skills within cross-functional engineering teams. Demonstrated ability to iterate quickly and continuously improve machine learning systems based on production feedback. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Principal Machine Learning Engineer to build and deploy production-grade machine learning systems that power its AI platform. This role focuses on translating research into scalable solutions by developing robust training pipelines, inference systems, evaluation frameworks, and deployment infrastructure. Working closely with research and application engineering teams, this position will play a key role in delivering reliable, high-performance ML systems that operate effectively under real-world production constraints. Key Responsibilities Build and own end-to-end machine learning pipelines covering data processing, model training, evaluation, inference, and deployment. Fine-tune and adapt models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation. Design and operate scalable inference systems while balancing latency, cost, and reliability. Develop and maintain data pipelines for both synthetic and real-world training datasets. Build evaluation frameworks to assess model performance, robustness, safety, and bias in collaboration with research teams. Optimize production deployments through GPU optimization, memory efficiency, latency reduction, and scaling strategies. Collaborate with application engineering teams to integrate machine learning systems into backend, mobile, and desktop applications. Continuously improve ML systems through rapid iteration and real-world performance monitoring while balancing production constraints such as latency, cost, reliability, and safety. Requirements Strong background in deep learning and transformer-based architectures. Hands-on experience training, fine-tuning, or deploying large-scale machine learning models in production. Proficiency with modern machine learning frameworks such as PyTorch or JAX . Experience with distributed training and inference frameworks, including technologies such as DeepSpeed, FSDP, Megatron, ZeRO, or Ray . Strong software engineering skills with experience building robust, maintainable, production-grade systems. Experience optimizing GPU workloads, including memory efficiency, quantization, and mixed precision. Ability to independently own end-to-end machine learning systems in fast-moving environments. Strong problem-solving skills with a focus on rapid iteration and continuous improvement. Preferred Qualifications Experience with one or more of the following is preferred: LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer Open-source contributions to machine learning or systems libraries Scientific computing, compiler technologies, or GPU kernel development Reinforcement Learning from Human Feedback (RLHF) pipelines, including PPO, DPO, or ORPO Training or deploying multimodal or diffusion models Large-scale data processing frameworks such as Apache Arrow, Spark, or Ray

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an iOS Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade iOS applications where AI interactions are central to the user experience, ensuring performance, reliability, and user trust across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable iOS applications that integrate advanced AI capabilities while maintaining a seamless and intuitive user experience. Key Responsibilities Build and maintain production iOS applications using Swift and SwiftUI . Integrate AI-powered features through backend APIs. Design user experiences for AI interactions, including loading states, streaming responses, retries, and fallback mechanisms. Optimize application performance, memory usage, and battery efficiency. Implement user feedback and analytics mechanisms to support AI evaluation and continuous product improvement. Collaborate closely with backend and machine learning engineers on API design and system behavior. Maintain high standards of application quality, stability, and reliability for App Store releases. Requirements Minimum 3 years of iOS development experience using Swift. Hands-on experience integrating AI-powered features into mobile applications. Strong understanding of async/await , concurrency, and background task management. Solid experience optimizing iOS application performance, memory usage, and responsiveness. Experience developing, releasing, and maintaining production iOS applications. Familiarity with designing applications that operate reliably under latency, partial failures, and non-deterministic AI behavior. Exposure to CoreML or lightweight on-device machine learning is an advantage. Familiarity with feature flags or remote configuration systems is preferred. Strong understanding of user experience design for AI-powered applications, with an emphasis on usability and user trust. Preferred Technical Skills Experience with the following technologies is preferred: Swift SwiftUI Swift Package Manager (SPM) SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is looking for a Full Stack Engineer – AI Systems to build AI-native product experiences that transform advanced AI capabilities into intuitive, production-ready workflows. This role combines frontend, backend, and AI engineering to develop intelligent features that are reliable, scalable, and user-centric. Working closely with product, backend, and machine learning teams, this position will focus on designing end-to-end AI workflows, integrating large language models (LLMs), and delivering seamless user experiences across web applications. Key Responsibilities Build end-to-end product features across frontend, backend, and AI integrations. Design and develop AI agent workflows that support planning, tool usage, failure handling, and recovery across multiple steps. Integrate LLMs, memory systems, and external tools into scalable, production-grade applications. Design responsive AI interactions with streaming capabilities, partial results, and low-latency performance. Improve system reliability, observability, and fallback mechanisms for AI-powered features. Collaborate closely with product, backend, and machine learning teams to deliver features from concept to production. Continuously iterate and improve product functionality based on user feedback, production insights, and real-world usage. Requirements Strong experience in full stack software engineering across frontend and backend development. Solid understanding of system design, scalable architecture, and API development. Experience building AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or similar technologies. Ability to work effectively in fast-paced environments with evolving requirements. Strong ownership mindset with experience delivering features from ideation through production deployment. Excellent problem-solving skills and the ability to make pragmatic engineering decisions in ambiguous situations. Preferred Technical Skills Experience with some or all of the following technologies is preferred: Next.js Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an Android Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade Android applications where AI is at the core of the user experience, ensuring performance, reliability, and usability across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable Android applications that integrate advanced AI capabilities while maintaining a seamless user experience. Key Responsibilities Build and maintain production Android applications using Kotlin . Integrate AI-powered features such as chat, vision, voice, and recommendation systems through backend APIs. Design intuitive user experiences for AI interactions, including streaming responses, retries, and partial results. Optimize application performance, memory usage, and responsiveness for AI-intensive workflows. Implement analytics, logging, and user feedback mechanisms to support continuous AI evaluation and product improvement. Collaborate closely with backend and machine learning engineers to define API integrations and system behavior. Ensure application stability, security, and scalability within production environments. Requirements Minimum 3 years of Android application development experience using Kotlin. Hands-on experience integrating AI-powered features, such as Large Language Models (LLMs), computer vision, or speech APIs. Strong understanding of asynchronous programming using Coroutines and Flow . Experience working with RESTful or gRPC APIs and structured data formats. Strong debugging, troubleshooting, and performance profiling skills. Experience developing applications that operate reliably under conditions involving latency, partial failures, and non-deterministic behavior. Familiarity with ML Kit or lightweight on-device inference is an advantage. Experience publishing and maintaining production applications on the Google Play Store . Preferred Technical Skills Experience with the following technologies is preferred: Kotlin / Java SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a AI Backend Engineer to build and operate the backend infrastructure that powers AI-driven experiences across its products. The role focuses on owning the inference and orchestration layer that sits between AI models and end users, ensuring every interaction is fast, reliable, scalable, and cost-efficient. Working closely with engineering and AI teams, this position will play a key role in designing production-grade backend services, optimizing system performance, and delivering robust AI-powered features across mobile and desktop platforms. Key Responsibilities Build, maintain, and operate backend systems that power AI-enabled features in production. Design and implement AI inference pipelines, orchestration layers, and service architectures around AI models. Develop scalable, high-performance APIs that integrate seamlessly with frontend applications and machine learning systems. Optimize system performance by improving inference latency, throughput, caching, batching, and streaming capabilities. Own production operations, including monitoring, logging, alerting, and incident response. Troubleshoot and resolve issues within distributed systems to ensure service reliability and stability. Continuously improve backend architecture and production systems based on operational insights and real-world usage. Collaborate with cross-functional teams to deliver reliable, scalable, and high-quality AI-powered solutions. Requirements Strong backend engineering experience in production environments. Proven experience building and operating high-throughput, low-latency backend services. Experience designing scalable APIs and distributed systems. Familiarity with AI inference patterns, including Large Language Models (LLMs), embeddings, and multimodal AI systems. Strong debugging and troubleshooting skills within distributed production environments. Demonstrated ability to deliver production-ready solutions while iterating based on real-world system performance. Excellent analytical, problem-solving, and collaboration skills. Technical Skills Experience with the following technologies is preferred: Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Pune, India About Flosum Flosum is at the forefront of innovation in the Salesforce DevOps ecosystem. Our comprehensive, Salesforce-native solution integrates version control, continuous deployment, automated merge tools, and deep code analysis—enabling development teams to move faster with confidence. Beyond DevOps, Flosum offers enterprise-grade Disaster Recovery and a cybersecurity framework purpose-built for Salesforce, empowering organizations to fully embrace DevSecOps. Our platform is trusted by developers, architects, admins, and CIOs to meet both technical and compliance demands—all within the Salesforce ecosystem. If you’re excited by the idea of contributing to a high-growth SaaS company with proven impact and powerful technology, we’d love to meet you. About You You’re an energetic, curious, and results-oriented individual eager to grow your career in tech sales. You’ve had early success in prospecting or sales development and are already used to carrying a quota and exceeding targets, now is the time to take your game to the next level. You thrive in fast-paced environments, are highly coachable, and bring both grit and empathy to your work. You are: Driven, self-motivated, and excited to learn. Organized and detail-oriented—able to manage your time and leads effectively. Collaborative and team-minded, with strong interpersonal skills. Comfortable with ambiguity and resourceful when facing challenges. Passionate about starting a career in SaaS or the Salesforce ecosystem. Bonus Points If You Have: Salesforce certifications or admin experience Familiarity with tools like Outreach, Cognism, Lusha, or Qualified Exposure to DevOps, cybersecurity, or Salesforce development environments Multilingual proficiency to support global outreach Requirements What You’ll Be Doing We’re growing our in-office team in Pune and we are building the sales team who will work closely with peers and sales leaders to build a qualified pipeline for our global sales teams. This role is Office based in Pune and the customers we are targeting will be largely in North American Time zones therefore you will need to be flexible to cover these hours. In this role, you will: Prospect into Salesforce customers via phone, email, and LinkedIn Respond quickly and professionally to inbound leads Qualify prospects by understanding their current challenges, goals, and fit Schedule discovery calls and demos for Account Executives Deliver the Flosum value prop clearly and creatively Keep Salesforce CRM up to date with clean, accurate activity and notes Follow internal processes and campaign playbooks to ensure visibility and reporting Stay current on the Salesforce ecosystem, Flosum’s product roadmap, and industry trends Work from our Pune office daily, collaborating with your manager and team Career Growth Path This role is built for ambitious professionals. High-performing BDRs will be considered for growth opportunities, such as Senior BDR or SMB Account Executive role, typically within 9-12 months. Promotions are based on demonstrated readiness for the next role and business needs, with clear coaching and development support provided along the way. Benefits Competitive compensation & incentive structure Daily coaching, mentorship, and growth opportunity Be part of a global, mission-driven team Learn from top leaders in Salesforce DevOps and SaaS sales Work on exciting challenges in a rapidly growing industry

Location: San Francisco, CA | 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 We are seeking a Director, Technical Accounting – M&A to join our Finance team at Anthropic. In this role, you will support the company's accounting for mergers, acquisitions, strategic investments, and other complex capital transactions. You will report to the Senior Director, Technical Accounting – M&A As Anthropic continues to scale rapidly and deploy capital into acquisitions, strategic investments, joint ventures, and novel commercial structures, you will be a key technical resource on structuring alternatives, consolidation outcomes, and financial statement impact. You will partner closely with Corporate Development, Legal, Tax, Treasury, FP&A, and leadership to ensure that deal economics are accurately reflected under US GAAP and that positions are defensible to external auditors, valuation specialists, and future regulators. This is a builder role: you'll help operate and continuously sharpen the controls, valuation governance, and close-ready documentation expected of a large accelerated filer, working alongside the Senior Director as the function takes shape. If you thrive on being in the room when deals are shaped — and then making the accounting land cleanly — we want to hear from you. In this role, you will: Execute technical accounting for business combinations, asset acquisitions, joint ventures, and related financing/equity structures Partner with and influence Corporate Dev to steer deal structures toward preferred terms and outcomes Perform accounting due diligence on prospective transactions, advising Corporate Development and leadership on GAAP, control, and earnings implications before terms are finalized Execute end-to-end purchase accounting — acquirer and acquisition-date identification, consideration measurement (contingent consideration, rollover equity, replacement awards), and recognition/measurement of assets, liabilities, and goodwill Execute post-close integration accounting — conforming accounting policies, system/ledger onboarding, working capital true-ups, earn-out remeasurement, and push-down considerations Assess and monitor consolidation and investment classification for investees and structured arrangements — VIE/primary-beneficiary analysis, reconsideration events, equity method, measurement alternative, and fair value through earnings — and support impairment and observable-price-change reviews Manage third-party valuation specialists; review PPA, intangible asset valuations, contingent consideration fair values, and impairment analyses Author and defend technical accounting policies & memoranda; partner closely with external auditors on M&A, investment, and consolidation matters Partner with Tax on deal structuring and ASC 740/basis-difference impacts; with Treasury and Legal on equity, SAFE/convertible, and other financing instruments Help refine the deal-accounting operating model — diligence checklists, Day-1 close playbooks, opening balance sheet procedures, measurement-period tracking, integration workplans, and SOX-ready controls over non-routine transactions Prepare and review transaction-related disclosures for quarterly and annual filings, including pro forma financial information and significance testing Present transaction accounting conclusions and financial statement impacts to leadership and cross-functional stakeholders in clear, decision-ready terms Monitor standard-setting and SEC developments affecting business combinations, consolidation, and investments; support adoption and cross-functional education You may be a good fit if you: Have 10+ years of progressive accounting experience, including 4+ years owning complex M&A and strategic investment accounting transactions end-to-end Hold an active CPA license Bring significant Big 4 experience — ideally in a National Office, Transaction/Deal Advisory, or Capital Markets/Accounting Advisory group — paired with in-house experience at a high-growth or public technology company Have contributed to multiple closed acquisitions and minority/strategic investments, including at least one transaction of meaningful scale or complexity Possess deep command of US GAAP for business combinations, consolidation, equity method, and fair value measurement, with a track record of positions that withstand auditor and regulator scrutiny Are fluent in valuation concepts and can direct and challenge third-party specialists on PPA, contingent consideration, and impairment models Have operated within a deal-accounting or investments-accounting function, contributing to playbook and controls design Communicate effectively with Corporate Development and Legal on structuring trade-offs, translating technical conclusions for cross-functional and senior stakeholders Demonstrate exceptional written and verbal communication, translating complex deal accounting into clear business implications Excel at hands-on technical execution in a fast-paced, ambiguous environment, partnering closely with the Senior Director on strategic judgment calls Are proficient with accounting systems (Workday preferred), consolidation tools, and advanced Excel/modeling Curious about and quick to adopt new AI tools, including Claude and Claude for Finance Strong candidates may also: Have deep, practitioner-level expertise in one or more of the following: Business combinations and asset acquisitions (ASC 805), including contingent consideration, replacement share-based awards, and step acquisitions Consolidation and investment classification (ASC 810, 323, 321), including VIE/primary-beneficiary analysis, basis differences, and the measurement alternative Fair value measurement, acquired financial instruments, and goodwill/intangibles (ASC 820, 815, 825, 350, 360), including impairment testing and IPR&D Have led accounting for carve-outs, divestitures, spin-offs, or legal-entity rationalizations, including standing up SOX-compliant controls over non-routine/complex transactions Have prepared or reviewed pro forma financial information and registration-statement disclosures (Article 11 of Regulation S-X, S-X Rule 3-05/1-02(w) significance testing, S-1 processes) Have experience with novel AI/technology deal structures — acqui-hires, IP/license-heavy transactions, data and compute arrangements, revenue-share partnerships, and strategic investor rights — and are passionate about leveraging AI to accelerate diligence, memo drafting, and close Deadline to apply: None. Applications will be reviewed 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: $230,000 — $300,000 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. 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: 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 Code RL at Anthropic drives reinforcement learning efforts behind Claude's coding capabilities, creating and scaling agentic coding environments. This is an engineering role with unusual latitude to set technical direction and standards. You'll be part of a team solving the engineering side of research efforts such as embedding with research teams, getting up to speed on their systems and needs, and designing the frameworks, APIs, and infrastructure that let researchers move faster, then rotating off, leaving behind well-oiled systems those teams can understand, own, and maintain themselves. Your remit also includes the ongoing health of production RL runs: maintainable, monitored, and straightforward to triage. The team's problem space spans the client side of sandboxed execution for agentic RL environments, large-scale data processing jobs, the lifecycle of production datasets, and the frameworks researchers build environments on. You won't own all of this yourself, you'll take on the slices where your depth matters most. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and hard-won intuition for how complex systems fail — especially silently. You should be comfortable diving into messy research code, finding the load-bearing abstractions, and improving them incrementally while researchers continue to build on top of your work. Key responsibilities Design widely-used APIs, frameworks, and abstractions that other engineers and researchers build on, with careful attention to interface legibility and principled defaults Embed with research teams on a rotational basis: understand their engineering needs, build systems and APIs that support their work, and transfer ownership so teams can maintain those systems after you rotate off Work directly in research codebases, improving reliability and structure without slowing down the research they support Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that shrink the surface area for bugs Contribute to the reliability of production RL systems, including monitoring, regression detection, and triage tooling Help define engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant Python code A track record of designing intuitive, safe APIs or frameworks that other engineers or teams adopted and built on Experience working productively in large, evolving, or research-style codebases that you didn't originally write Demonstrated ability to anticipate failure modes — especially silent ones — and prevent them structurally through system design, type safety, and testing Strong written and verbal communication skills, including the ability to explain system designs to collaborators with varied engineering backgrounds Comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows Familiarity with reinforcement learning concepts, agentic systems, or LLM training pipelines Experience building or operating large-scale distributed systems Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing or dataset lifecycle management Experience designing plugin systems or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams, including successfully handing off systems for others to own Experience defining code standards, lint rules, or static verification approaches adopted across multiple teams Prior experience as a technical lead, or setting engineering standards for a team Prior experience maintaining an open source project Representative projects These are examples of the challenges the team tackles; no one person will work on all of them: Design a base RL environment abstraction general enough to be subclassed across a wide range of environments Design a model-tool interface for sandboxed agentic environments that has explicit serialization semantics Partner with the platform teams that own the sandbox runtime to specify low-level features that improve the integrity of agentic coding tasks Design probes that catch sandbox regressions early Design the lifecycle and maintenance scheme for a production dataset Lead a research code refactor replacing loosely structured data containers with equivalents that carry stronger correctness guarantees, without breaking the experiments that depend on them Design lint rules and code-style requirements that favor statically verifiable patterns — including patterns less likely to be overlooked by an LLM reviewing or writing the code — to shrink the surface area for silent bugs Build the access layer that lets researchers discover and reuse data artifacts across teams 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: $405,000 — $625,000 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. 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: San Francisco, CA | New York City, NY 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 Anthropic's Environments organization builds and maintains the infrastructure that improves Claude’s capabilities through reinforcement learning. That includes the frameworks researchers use to build environments and the infrastructure responsible for running them. The team's mission is to productionize research. You'll embed with research teams, get up to speed on how they work, and design the frameworks and APIs that let them move faster, building systems the team can understand, own, and maintain themselves. Scope also includes keeping production RL runs healthy, maintainable, monitored, and easy to triage. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and good intuition for how complex systems fail, especially silently. It's a bonus if you've built and operated a stateful distributed system, such as a workflow engine, actor framework, or durable-execution runtime, where correctness depends on getting shared state and recovery right. You should be comfortable diving into messy research code, finding the abstractions that matter, and improving them incrementally while researchers continue to build on your work. You should also be comfortable using AI tools to accelerate your own development, but have an impulse towards deep verification. Key responsibilities Design widely used APIs, frameworks, and abstractions that other engineers and researchers build on, making correct usage the default and ruling out entire classes of errors structurally Own the platform layers that sit beneath every environment, including the agent runtime Build the tooling that lets environment owners understand, debug, and maintain their environments in production without needing an infrastructure engineer in the loop Embed with research teams on a rotational basis, work directly in their codebases without slowing down the research they support, and transfer ownership when you rotate off Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that reduce the room for correctness issues Drive adoption of new frameworks across the organization, including deprecations and cutovers Help define the engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant code Strong taste in API and framework design, the ability to explain why an interface is right or wrong rather than just recognizing it, and a track record of other engineers or teams adopting and building on frameworks you have built Experience designing or operating stateful concurrent or distributed systems, and reasoning carefully about failure, retries, idempotency, and consistency A habit of verification: you measure before you conclude, and you build the checks that let a system show it's correct Experience working productively in large, evolving, or research-style codebases that you didn't originally write Strong written and verbal communication with collaborators of varied engineering backgrounds, and comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows, and familiarity with agentic systems or LLM training pipelines Experience building agent frameworks, orchestration engines, or multi-agent systems, including checkpoint and restore, replay, and coordination of long-running stateful processes Experience using AI coding tools on code where correctness matters, with good judgment about what to delegate and how to make the results verifiable Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing, dataset lifecycle management, or data lineage systems Experience designing serialization schemes, plugin systems, or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams and handing off systems for others to own, or defining code standards adopted across teams, or prior experience as a technical lead Representative projects These are examples of the challenges the team tackles: Design a base RL environment abstraction that can be subclassed to support the large majority of environments built across RL Redesign the model-tool interface for sandboxed agentic environments so that state is guaranteed to survive serialization, making it structurally impossible to write a tool that silently loses state Design the state-sharing and recovery model for multi-agent workloads, so that losing a sandbox partway through a task becomes a transparent resume rather than lost work Define the failure and retry model for a sandboxed execution platform, distinguishing infrastructure faults from genuine task outcomes so that each is handled correctly Build the tooling that lets an environment owner diagnose why their environment is unhealthy in a production run, and fix it themselves 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: $405,000 — $605,000 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. 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) Workplace: Remote ABOUT ONEPAY OnePay is the consumer fintech trusted by millions of Americans to make money better. Our financial system is broken. High fees, low rates, and too few ways to actually grow your money. We’re fixing it. And we’re moving fast. We’re an all-in-one financial services platform that brings together banking, high-yield savings, credit cards, point-of-sale lending, investing, and crypto in one place. We also partner with employers, HCM providers, gig platforms, and others to deliver embedded financial services to millions of employees and frontline workers. We’re backed by Walmart, the world’s largest retailer, and Ribbit Capital, one of fintech’s most respected investors, giving us rare scale, distribution, and the opportunity to build something truly category-defining. But what really sets OnePay apart is how we move. Our customers don’t have time to wait… and neither do we. This place moves fast, and we’re looking for people who are: - Ready to run - Hungry and driven by urgency - Exceptional at what they do, with low ego - Comfortable operating in motion THE ROLE As a Platform Engineer on the Builder Experience Team at OnePay, you will build the core platform services and developer frameworks that power large-scale, distributed systems and enable the next generation of intelligent, agent-driven applications.   WHAT YOU’LL DO - Design and operate platform-oriented core services that support high-scale distributed systems across OnePay’s product ecosystem - Develop internal developer tooling and shared infrastructure that improve velocity, reliability, and observability across engineering teams - Build and evolve frameworks that support the construction and orchestration of agentic applications, enabling intelligent, automated workflows across products - Drive enhancements in CI/CD pipelines, automation, and developer workflows to increase deployment speed, reliability, and confidence across teams   YOU BRING - 2-9 years of experience in software engineering within fintech, cloud infrastructure, or large-scale distributed systems environments - Experience building developer platforms, internal tooling, or frameworks that enable other engineers to move faster - Deep expertise in distributed systems, asynchronous processing, and high-availability platform services - Production experience in AWS cloud environments and building cloud-native infrastructure - Demonstrated experience designing and building agentic developer tools that empower automation, collaboration, or intelligent workflows - Strong experience working with CI/CD pipelines and driving continuous integration and delivery improvements - Drive and proactivity – everyone here is a builder and executor TOOLS WE USE We use Typescript front to back, with node and NestJS frameworks for server code and React Native for our iOS, Android, and Web clients. We run on a highly distributed cloud-native stack with Kubernetes and AWS, and scale and resiliency are at the heart of everything we build. We also embrace agentic development, so engineers have their choice of a variety of models and agent harnesses, including Claude Code, Cursor, Codex, and more to fit their workflow. While you don't need experience with our exact stack, familiarity with modern software engineering practices will help you ramp up quickly. WHAT WE OFFER - Competitive base salary, stock options, and health benefits from Day 1 - 401(k) plan with company match - Remote-friendly (US), flexible time off (FTO), and opportunities for growth - A high-growth, mission-driven, inclusive culture where your work has real impact STANDARD INTERVIEW PROCESS Our process varies by role. Most candidates go through: - AI-assisted initial screen - Interview with Talent Partner - Technical or Hiring Manager Interview - Team Interview - Executive Interview - Offer! EQUAL EMPLOYMENT OPPORTUNITY To build technology and products that are used and loved by people and solve real-world problems, we need to build a team with many different perspectives and experiences. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us at talent@onepay.com.

Location: Remote - US Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Sr AI Architect - Conversation AI. About the job This position is critical to leveraging Twilio’s massive data ecosystem and unmatched communication scale to build our customer facing AI capabilities, such as Twilio Conversational Memory, Enterprise Knowledge, Behavioral Data Intelligence and many more to power the future of our customer engagement platform. As a Sr. AI Architect for Twilio Platform, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. You will drive cross-organizational initiatives, solve complex technical challenges, and elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission. As a Sr AI Architect, you will lead the company as the Distinguished Engineer and AI Contextual Engineering SME, serving as the guiding authority to our Architects, driving company-wide impact, and steering Twilio's overarching technical direction for conversational AI. In this pivotal leadership role, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. By driving cross-organizational initiatives and solving complex technical challenges, you will elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission. Responsibilities In this role, you’ll: Define and drive a long-term AI/ML architectural vision that aligns with Twilio’s business goals, specifically focusing on how data and memory power the next generation of customer engagement. Own the strategic roadmap for Twilio’s ML/AI Ops platform and tooling, ensuring a unified approach to model development, deployment, and lifecycle management across all platform capabilities. Evaluate and implement modern LLM architectures, RAG systems, MCP/tooling frameworks, and inference optimization techniques. Lead architecture for agentic AI systems including orchestration, reasoning, tool usage, and contextual grounding. Stay current with rapidly evolving advancements in LLMs, agent frameworks, reasoning systems, and AI infrastructure. Transition seamlessly from high-level strategic communication with executives to deep-dive code reviews and pair programming with engineers. Partner closely with Product Management to turn a roadmap into a sequence of technical milestones, ensuring that technical investments always map to customer value. Have a 'player-coach' mentality, and contribute hands-on technical expertise while providing strategic direction and mentorship to the team. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! Required: 15+ years of experience in software engineering, with at least 6+ years specifically focused on building and scaling production-grade ML systems at a platform level. Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics, automated retraining loops, and monitoring for non-deterministic AI features at scale. Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including deep knowledge of transformer models, LLM orchestration, embedding models, inference optimization and vector stores. Deep understanding of the Context Engineering lifecycle, including semantic retrieval, contextual compression, state management across multi-turn conversations. Strong background in building cloud-based services using AWS, GCP, or Azure, with experience managing high-volume data and various data stores. Exceptional communication and collaboration skills, with a proven ability to mentor engineers, influence company wide technical strategy, product direction, and drive results across the company. A Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a closely related quantitative field. Desired A track record of relevant publications at top ML conferences or significant open-source contributions. Experience designing evaluation frameworks that specifically measure context quality Track record of designing and implementing enterprise-scale ML/AI Ops platforms Experience working in a geographically distributed environment. Location This role will be remote and based in the United States. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 5% travel is anticipated to help you connect in-person in a meaningful way. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Compensation Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only. The estimated pay ranges for this role are as follows: Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $275,840.00 - 344,800.00. Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $292,080.00 - 365,100.00. Based in the San Francisco Bay area, California: $324,480.00 - 405,600.00. This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Application deadline information Applications for this role are intended to be accepted until October 30, 2026 but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

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're standing up a dedicated executive support function within IT, and we're hiring the IT Support Engineer who will build it. IT Support is the front door for every employee technology need at Anthropic, and this role creates its most visible lane: white-glove support for our executives, their administrative business partners (ABPs), and our board. You'll define what that service looks like: the support model for execs, board, and ABPs, the runbooks behind it, the intake and escalation paths, and the trusted relationships with ABPs and exec staff that make it work. You'll set the bar for discretion and polish as you go. You'll also be the person our leadership reaches when technology gets in the way. The requests that land in this lane range from routine to highly sensitive, and many arrive urgent: an executive locked out minutes before a meeting, an AV issue in a room full of leadership, a board member who needs setup handled quietly and correctly the first time. You own the request end to end and pull in specialist functions or IT Engineering pods as needed. Responsibilities Stand up the executive support intake channels and run it: monitor, respond, and follow through on every request from executives, ABPs, and board members Define the white-glove service model for discretion-sensitive asks and deliver to it, holding confidentiality under pressure Design the board-meeting AV support playbook with the AV pod, and provide AV support for executive rooms and board meetings, from setup and pre-checks through live triage Create exec-support runbooks and SLAs that keep the service consistent as it grows Build trusted relationships with ABPs and executive staff, and establish clear intake paths so leadership knows exactly where to go Handle ABP escalations and exec-urgent issues calmly, and route into specialist lanes or IT Engineering pods when a request needs them Establish the board member device, account, and access setup process with our Onboarding lane Work the shared ticket queue with the SF Core team: walk-ups, desk-side help, hardware swaps, it-assist overflow, and AV T1 triage Participate in the Core on-call rotation and contribute to the knowledge base and runbooks Maintain a regular on-site presence in San Francisco You may be a good fit if you have 7+ years of experience in IT support and 3+ years in executive support Experience standing up a service or program from scratch, such as an executive support desk, a VIP support function, or a white-glove service Experience supporting executives, their assistants, or a board to a white-glove standard A track record of handling sensitive requests with discretion, and the judgment to know what stays confidential without being told Strong hands-on IT support fundamentals: macOS-primary fleets, identity and access, SaaS troubleshooting, hardware lifecycle AV fluency for executive rooms and board meetings: you can set up, verify, and fix a room under time pressure Composure when an urgent escalation lands, and the judgment to know when to pull in help High polish and low ego: you take pride in service quality and still pick up whatever the team needs, including the ordinary queue work A security-first mindset and excellent judgment about when user experience yields to security requirements Comfort with ambiguity: you can make progress before the process exists, and you enjoy shaping how things should work The instinct to write things down: runbooks, KB articles, and status updates that keep people informed Nice to have Experience supporting a C-suite or board of directors at a company with significant security or compliance requirements AV depth beyond first response, such as broadcast, live events, or room design input Experience building runbooks, self-service content, or support automation Experience supporting AI/ML research environments or highly technical user bases 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: $180,000 — $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. 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: Montreal, Canada Role Overview: As a Senior PCB Design Engineer, you will take on a leadership position within our hardware design group. Your key duties will revolve around crafting, executing, and validating mixed-signal (Digital & RF) Printed Circuit Boards (PCBs) customized for application in satellite and other orbital systems. These applications encompass a diverse spectrum, encompassing digital control/processing,  motor drive units,  onboard processors,  and mass-storage units, all of which utilize cutting-edge space technologies. Key Responsibilities: Lead the digital/analog PCB design for space environments. Mentor and oversee junior team members and interns in PCB design. Translate board-level requirements into a comprehensive design concept (incorporating architecture, I/Os, key components, power dissipation estimates, FPGA integration, software integration, etc.). Collaborate closely with FPGA, software, and test designers to finalize functional concepts and streamline integration. Complete or review the schematic capture level design. Identify and manage technology and design risks. Provide guidance to ensure Design for Manufacture/Test in space environments. Supervise and review design layout constraints, parts placement, manufacturing, and assembly drawings. Prepare or review lists of long lead items, bills of materials, and ensure parts qualifications for space. Conduct and review circuit simulations (using tools like SPICE, Hyperlynx, ADS, etc.) and various design analyses (e.g., worst-case scenarios, FMECA). Coordinate with various specialized teams (structural, thermal, packaging, manufacturing, quality assurance, etc.) to conduct necessary reviews for PCB component placement and layout. Oversee board assembly and manufacturing tests. Prepare and review various documents, including review presentations, test plans, test procedures, etc. Lead and guide junior team members in testing, troubleshooting, and debugging complex mixed-signal boards. Provide support for environmental and functional tests and validation for space missions. Report progress and address issues to the program lead or manager. Required Qualifications: Bachelor’s degree in electrical engineering, computer engineering, or equivalent field. Minimum of seven (7) years of experience in designing processor, digital, analog, high-speed, or mixed-signal PCBs. Demonstrated expertise in at least one of these areas of competence. Proficiency in coaching and supervising junior team members and interns. Experience in design architecture and handling multidisciplinary specifications and reviews (FPGA, software, mechanical, etc.). Proficiency in tools/software languages such as Excel spreadsheets, Python, MathCAD, Spice, Matlab, JIRA, etc. Strong understanding of electronic circuits and communication protocols, coupled with extensive PCB design experience. Knowledge of PCB manufacturing processes. Exposure to mechanical packaging is a valuable asset. Experience conducting analyses (FMECA, WCA, signal integrity, power integrity, etc.) using various tools like SPICE, ADS SiPro, Hyperlynx, etc.

Location: Oakland, California, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role If the idea of contributing to the critical and core services that drive the fundamental functioning and building blocks of data processing involved in our data pipelines, this opportunity fits you well. As an engineer on the core team, you will design,  implement, and maintain the central parts of our data pipelines needed to operate the best-in-class reliable, secure, and scalable data movement.  You will prioritize the quality, efficiency, and reliability of the responsibility areas of the team while collaborating effectively with other peers and the rest of the engineering organization. The ideal candidate exhibits exceptional technical skills, meticulous attention to detail, creativity, motivation, and a results-oriented mindset. This is a full-time hybrid position based out of our Oakland office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Java17, JUnit5 Docker and Kubernetes AWS, GCP, Azure SQL, BigQuery Bazel, BuildKite What You’ll Do Design and implement features and performance improvements to create highly scalable distributed data pipelines on the cloud Develop, maintain, and test code Conduct design and code reviews Collaborate with peers, product managers, customer support, and other stakeholders to deliver the best product with high quality, performance, and scalability. Understand and fix challenges related to performance and scalability. Participate periodically in on-call rotation Participate in the hiring process Mentor Junior developers Make Fivetran the most reliable and secure component of our customers’ data infrastructure Skills We’re Looking For 5+ years of experience in the software industry with a passion for solving complex software engineering problems. Software engineering foundation - experience designing and developing reusable libraries and experimentation platforms for backend and frontend from scratch leveraging industry best practices. Experience working with distributed systems Demonstrated ability to write well-structured and performant code Ability to lead software design to satisfy project requirements Experience in code reviews, design, troubleshooting and testing Experience programming in an object oriented / systems language such as Java, C++, C# etc Hands-on experience working with any cloud technologies(AWS, GCP, Azure) and containerization methodologies like Docker, K8s Experience interacting with continuous integration tools like Buidkite Bonus Skills​ Knowledge of observability tools like New Relic/Grafana is a plus Knowledge of AI tools and usage is a plus #LI-HYBRID #LI-EM1 The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Oakland Pay Range $174,915 — $209,906.50 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: New York, NY • United States Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! At Figma, we're building tools that help teams design, build, and ship better products together. Figma Make enables teams to go from prompt to production code, and the Figma agent is a purpose-built design agent that edits files directly on the Figma canvas. We're looking for a deeply technical product leader to lead the four teams responsible for Figma's Roundtripping area: Code Context, Design to Code, Code to Design, and Code Platform. You'll manage and grow a team of Product Managers while partnering closely with engineering, design, data, and research leaders. This team builds the products and platform capabilities that help design and code move fluently together. You'll set the strategy for improving connecting customer codebases to Figma. This is a full-time role that can be held from our New York hub or remotely within the Eastern US time zone. What you'll do at Figma: Lead the product aspects of the four teams driving Figma's Roundtripping area - Code Context, Design to Code and Code to Design, and Code Platform Set vision, strategy, and goals for how design and code stay in sync at Figma Own Design to Code and Code to Design workflows end to end, including quality measurement, improvement, and discoverability Guide the development of the code-context systems and translation primitives that power agentic workflows and round-tripping between design and code Manage and develop three Product Managers, hire the team's open Product Manager role, and establish a high bar for product management craft Partner with leaders across engineering, design, data, and research to make technical product decisions and serve needs across Figma's product suite Establish a strong operating cadence across the area and own adoption goals for MCP and Design to Code/Code to Design workflows We'd love to hear from you if you have: 3+ years of experience managing Product Managers, with a proven track record of hiring, calibrating, and developing talent Deep experience shipping developer tools and AI products - has run evals, owned annotation pipelines, and made real ship/no-ship calls on model behavior A track record of setting strategy and executing on major initiatives in environments with deep technical and product ambiguity - and rallying an org around a bold, unproven bet Experience working with enterprise customers to understand their workflows and turn that into shipped product Excellent cross-functional collaboration and written communication with technical depth; credible in engineering reviews and with senior stakeholders At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Annual Base Salary Range: $204,000 — $348,000 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.