Вакансии

Задачи: — Разработка масштабируемых платформ управления облачной инфраструктурой. Требования: — Опыт работы с Kubernetes, Java, C#, Go, Rust. — Знания в области управления конфигурациями, распределённых систем, автоматизации, облачной безопасности и обеспечения доступности и масштабируемости систем. Условия: — Работа в офисе в Сан-Франциско, Калифорния, США. Зарплата: $209,000 - $253,000 в год.

Crusoe is looking for a Staff Network Engineer Storage to architect and operate a high-performance storage network.

Crusoe is looking for a Senior Staff Software Engineer Storage DPU to design and build DPU-offloaded storage software.

Crusoe is looking for a Staff Kernel Security Engineer to harden Linux kernel and operating-system components.

Location: United Kingdom, Remote Workplace: remote Olo is a leading SaaS platform accelerating digital transformation in the restaurant industry, by helping customers deliver more personalised and profitable guest experiences. As a result, our digital ordering, payment, and guest engagement solutions enable brands to do more with less and make every guest feel like a regular.   Reporting to the Security Engineering Director, the Staff Security Engineer will act as technical lead of the Olo Security Blue Team and work on security defences that allow our systems to keep running while protecting the data of our clients and their customers.   Additionally, you will help in the identification and prioritisation of future project initiatives based on risk and execute cross-functional projects with a high degree of ownership and excellence, all while actively mentoring other team members and elevating the collective team’s capabilities and skill sets. If you are passionate about reducing risk while supporting innovation, we encourage you to apply!   You can work remotely from anywhere in the United Kingdom. How you’ll make an impact Guide and coach Olo’s Blue Team on Information Protection, Incident Detection and Response and Service Delivery. You will provide strategic and technical oversight to the team and the program. Technically lead a team of security engineers and analysts who hunt, detect, and respond to internal and external threats. Collaborate with customers and partners to strengthen their security posture. Drive ongoing optimisations by implementing new technologies, replacing technologies, addressing evolving threats, scaling practices and automating security activities. Ultimately you will keep team member and customers data safe by identifying and mitigating vulnerabilities and risks by providing actionable guidance to product teams. Information Protection Lead Olo’s Information Protection program including the selection, testing, implementation and maintenance of security tools and services, security awareness, service provider management and the ongoing testing of those controls. Oversee Vulnerability Management program including vulnerability assessments, risk scoring and vulnerability resolution. Oversee Threat Hunting program to detect and mitigate advanced threats. Manage non-event driven security reviews, including concept reviews, design reviews, patching, firewall rules and system configuration checks. Apply Web application and API security principles and techniques, such as zero trust, RBAC, authentication, authorization, auditing, rate limiting, challenges, etc., to protect our cloud-based services from unauthorized access and abuse. Incident Detection and Response Oversee Incident Detection and Response program including ownership of incident response processes, tools and services and the ongoing continuous improvement of those controls. Coordinate the detection and response to attacks through all incident phases. Ensure incident reports are accurate, detailed and relevant. Monitor, detect, and remediate misconfigurations and security risks across our cloud environments. Participate in a 24/7 on-call rotation. Security Services Oversee Security Services program including security support requests, risk assessments, vendor assessments, PCI and SOC audit support and service provider management. What We'll Expect from You 5+ years of Security Engineering, Security Operations or Security Architecture experience. CISSP, GCIH or similar certification preferred. Experience acting as technical lead to distributed teams consisting largely of remote engineers. Experience complying with PCI-DSS and other compliance and regulatory standards. Experience with attacker tactics, techniques and procedures. Knowledge of information technology, evolving threats, attack patterns, incident response and cyber security standards. Experience developing and leading incident response, remediation and mitigation activities, and providing status updates and reports. Experience analyzing security events to discern events that qualify as a legitimate security incident as opposed to non-incidents (ie. incident investigation, implementing countermeasures, and conducting incident response). Deep understanding of operating system, networking and application concepts. Experience hardening Windows, MacOS, Linux Containers and Kubernetes. Familiarity with AWS security best practices and Infrastructure-as-Code. Experience deploying and maintaining security technologies. (e.g. Access Proxies, API Gateway, Anti-Malware, Application Control, Cloud Security Posture, Data Leak Prevention, Data Mapping, Endpoint Detection & Response, Intrusion Detection System, File Integrity Monitoring, Firewalls, Mobile Device Management, Multi Factor Authentication, SIEM, Static Inspection, Vulnerability Assessment, Web Proxies, WAF and Zero Trust). Adept at working with internal Product & Engineering, Legal, People & Culture, Finance and GTM teams and external partners, auditors and customers. Ability to work during critical incidents or to support coverage requirements. About Olo Olo is a leading restaurant technology provider with ordering, payment, and guest engagement solutions that help brands increase orders, streamline operations, and improve the guest experience. Each day, Olo processes millions of orders on its open SaaS platform, gathering the right data from each touchpoint into a single source—so restaurants can better understand and better serve every guest on every channel, every time. Over 800 restaurant brands trust Olo and its network of more than 400 integration partners to innovate on behalf of the restaurant community, accelerating technology’s positive impact and creating a world where every restaurant guest feels like a regular. Learn more at olo.com. Applicant Privacy Notice (United Kingdom)

Location: Amsterdam, Netherlands; Berlin, Germany; London, United Kingdom; Poland; Prague, Czech Republic; Zurich, Switzerland About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Role Summary Nebius Token Factory is building production-grade inference for open-source, customer, and internally optimized models. This role owns the path from model artifact to fast, reliable, cost-efficient endpoint. The work sits at the intersection of model internals, inference engines, serving architecture, benchmarking, and production deployment. What You Will Do Own a platform-level optimization pillar such as quantization, speculative decoding, KV -cache optimization, engine selection, or long-context serving. Create reusable evaluation, benchmarking, and rollout frameworks across multiple model families. Provide technical direction to MLEs, Applied Scientists, GPU kernel engineers, and infrastructure engineers on shared performance goals. Optimize LLM and VLM endpoints for latency, throughput, memory efficiency, GPU utilization, quality, and cost per token. Deploy, configure, benchmark, and extend inference engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, or similar systems. Build and productionize model-compression workflows, including quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery. Implement or integrate speculative decoding, draft-model approaches, KV -cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving. Build reproducible benchmark harnesses for TTFT , TPOT , tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token. Partner with GPU kernel engineers and platform engineers to diagnose bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers. Write clear design docs, performance reports, rollout plans, and customer-facing technical explanations. Required Qualifications Strong Python and PyTorch engineering skills. Hands-on experience deploying or optimizing LLM, VLM , or high-throughput transformer inference systems. Practical knowledge of at least one modern inference stack such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or equivalent internal systems. Strong understanding of transformer inference bottlenecks, including KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving. Ability to reason quantitatively about latency, throughput, quality, utilization, and cost tradeoffs. Strong communication skills and ability to collaborate with research, kernel, infrastructure, product, and customer teams. Preferred Qualifications Experience with quantization-aware training, post-training quantization, FP8 , INT8 , INT4 , NVFP4 , MXFP4 , AWQ , GPTQ , SmoothQuant, or related techniques. Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or other inference acceleration methods. Experience with agentic workloads, including tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. CUDA or Triton familiarity, even if the role is not primarily a kernel-engineering role. Open-source contributions to vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, KServe, or related projects. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

* Act as a key technical leader across site reliability, platform architecture, and infrastructure scaling. * Experience in effectively designing and operating large-scale cloud environments in a platform, SRE, or architecture team, with a focus on enabling self-service capabilities and a great user experience.

Crusoe is looking for a Senior Staff Program Lead Cloud Engineering Operations to lead operating programs, metrics, and accountability across cloud engineering.

Crusoe is looking for a Senior Staff Optics Engineer Network Qualification and Strategy to qualify optical interconnects and define data-center optics strategy.

Crusoe is looking for a Senior Staff Linux Security Engineer to harden Linux kernel systems and lead vulnerability remediation.

In This Role You Will: Design zero to one agents. New writing and communication agents, built as AI-first products.

We are seeking a strategic and analytical Chief of Staff to partner with our Chief Customer Officer (CCO) in driving business performance across our Customer organization.

Location: Remote; Seattle, WA; New York, NY; San Francisco, CA Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE *Open to hiring remote across the US — we also have offices in New York, San Francisco, Seattle, London, Paris, and Tel Aviv. Runway is rapidly building the leading ecosystem of generative models, bringing the best models from AI labs around the world to our users alongside our own. We are looking for an IC to source, activate, and scale relationships across Runway's growing portfolio of model partners. This is a role for someone who wants to own whatever needs owning, take new models from first conversation to launch, and write the playbook where none exists yet. You will work closely across Engineering, Product, Legal, Finance, and Marketing. WHAT YOU'LL DO - Own a broad portfolio of model partners end to end, across modalities - Track the model landscape relentlessly: spot new labs and releases early and bring the strongest ones to the team as candidates for integration - Take new partners from zero to launched: source, structure and negotiate commercial terms, then close with Legal and Finance - Be the partner's main point of contact through launch, working closely with our engineering team - Build deep, trusted relationships with founders, BD leads and research teams at our partners, and turn those relationships into early access, better terms and joint launches - Run the portfolio with rigor: set check-in cadences, monitor relationship health, and spot and escalate risk early - Track usage, spend and margin by partner and model, and use that data to decide where to invest, renegotiate or step back - Partner with Marketing and our partners on co-marketing for model launches - Build the frameworks and tools that let the function scale as the ecosystem grows WHAT YOU'LL NEED - 5+ years of experience across some combination of partnerships, business development, GTM, consulting, or founding/operating, with a track record of having owned outcomes end to end - Experience negotiating commercial agreements, ideally usage-based, API or platform deals - Genuine obsession with generative AI: you know the labs, you try new models the day they ship, and you have opinions on what makes one good - Demonstrated range: you've done the deal and the integration and the launch - High technical aptitude for understanding complex technologies, tools, systems, and issues - Strong analytical capabilities, with the ability to turn usage and spend data into a clear recommendation - Ability to manage many relationships and priorities at once in a fast-paced environment without dropping threads - Clear, concise communication, from a startup founder to a big-lab partnerships team to a Runway engineer in the same day - A strong bias towards action and belief that no task is too small for you - Highly resourceful, with the ability to create structure and work autonomously amid ambiguity - New York-based preferred Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: San Francisco; New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW As a Backend Platform Engineer at Harvey, you will help build and operate the cohesive backend platform that all our services run on. You’ll design and implement shared frameworks and libraries that abstract common concerns, improve developer experience, and raise the baseline for reliability and performance across all teams. Your mission aligns with our platform charter: create “a shared foundation that enables product teams to ship reliable, observable, and performant experiences quickly and safely.” By centralizing common work, you’ll let product engineers focus on shipping features rather than re-inventing the wheel. This is a high-impact role where the code you write and the systems you build will amplify the productivity and quality of engineering across the entire company. If you’re excited about building foundational systems, solving cross-cutting technical challenges, and enabling others to move faster with confidence, we’d love to hear from you. WHAT YOU'LL DO - Develop and maintain Harvey’s internal backend frameworks and libraries that provide common capabilities (API routing, service lifecycle management, caching and messaging primitives, error handling interfaces, etc.), so product teams don’t have to reinvent them - Create and improve APIs, service templates, and versioned interfaces that establish consistent patterns for building new services and features - Introduce and champion modern backend architecture patterns like asynchronous I/O (asyncio) and streaming data processing, continually evolving our platform for better performance and scalability - Design Harvey-specific abstractions and domain-specific frameworks—covering cross-cutting concerns (e.g., authorization, streaming) and areas like data governance and event processing—to provide product engineers with these capabilities out of the box - Embed reliability and observability into the platform by building in tracing, metrics, and automated tests (shift-left), ensuring services built on our foundation are robust and easy to monitor - Collaborate with Model Infrastructure team to tackle challenges unique to GenAI-native applications — such as supporting high-throughput model inference, managing streaming and long-running API interactions, and designing abstractions for retrieval, context handling, and prompt lifecycle - Collaborate with the Developer Experience and Infrastructure teams (who own CI/CD pipelines, build tools, and release infrastructure) to integrate our platform components seamlessly into the deployment and monitoring ecosystem - Work closely with product engineering teams to gather feedback, evangelize best practices, and make the “paved road” approach a reality — providing strong defaults and clear documentation so teams can move fast with confidence WHAT YOU HAVE - 8+ years of software engineering experience (post-BS/MS), including building scalable backend systems or internal developer platforms - Proficiency in Python (or similar languages) and deep knowledge of backend development fundamentals (APIs, data stores, concurrency, distributed systems) - Hands-on experience with web frameworks and service architectures (e.g. Flask/FastAPI, Bounded context services, microservices) and an understanding of designing clean, versioned APIs - Familiarity with caching, messaging, and database technologies (Redis, Kafka, SQL/NoSQL databases, Vector databases, etc.) and how to use them effectively for high performance and reliability - A track record of writing high-quality, well-tested code and using tools (unit/integration testing, static typing, CI) to catch issues early and ensure reliability - Strong problem-solving skills and a passion for improving developer experience — you enjoy creating tools or frameworks that make other engineers more productive - Excellent collaboration and communication skills, with the ability to work across teams and incorporate feedback. - Experience contributing to or maintaining internal libraries/frameworks is a plus. COMPENSATION RANGE $231,000 - $340,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES [HERE https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922]. #LI-AN2 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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 Platform Safety builds the infrastructure that lets Anthropic bring its most capable models to more people, safely and securely. Our systems decide both who can access our most advanced models, and what capabilities they can access, wherever Claude is available. That includes identity and business verification, trusted access programs, and the core services that grant, hold and enforce model access across our products. These systems already power the Cyber Verification Program, which now includes Project Glasswing, and the Life Sciences Verification Program with further more advanced use cases in development. As a Staff+ engineer, you'll help set the technical direction for this work. The foundations are live and adoption is growing quickly, so the next challenge is scale: making access a matter of configuration instead of code, making verification reusable, and giving customers a consistent experience on every surface. You'll work closely with safeguards, product, design and research to turn safety policy into systems that are easy to use and enforce. You'll also take new 0 → 1 efforts from idea to delivery as new capabilities and programs emerge. What you'll do You'll design, build and operate the systems that decide who gets access to our most capable models. You'll build the platform that lets teams across Anthropic launch and run trusted access programs, moving access rules out of code and into data so that launching a new model or complex program is simple and scalable. You'll build out our identity and business verification system (KYC/KYB) as a reusable service that any program can use, which means integrating verification vendors, protecting sensitive personal data, expanding into new regions, and building fair review and appeal paths for customers. You'll also evolve the core services behind every access decision, including the services that grant and hold access and the customer and user identity models they rely on, and keep them highly available and consistent across our own products and cloud platforms. You'll shape the architecture through clear written proposals, review key designs, and mentor engineers on a growing team. You'll also share on-call, lead incident response, and support emerging new programs. You might be a good fit if you: Have a minimum of 8 years of practical experience as a backend or platform engineer, ideally at tech lead level or equivalent, and are comfortable working across the stack when the problem calls for it Have strong product sense, and work closely with cross-functional partners, including non-engineers, to shape and execute strategy in new domains Use AI tools as a regular part of how you design, build and review software Have designed and operated production distributed systems on a critical path, where correctness, latency and availability all matter Take full ownership of your work, from design through build, deployment, operations and iteration Navigate ambiguity and make sound technical decisions independently, have set technical direction that other engineers and teams adopted, and have ideally operated in both 0 → 1 and more mature settings Care about building robust, scalable systems that other engineers and businesses love to use Care about the societal impacts of your work and Anthropic's mission to build safe, beneficial AI Strong candidates may also have: Identity, access control or authorization systems at scale Fraud, risk, trust and safety, or KYC/KYB systems, including working with verification vendors Regulated or compliance-sensitive environments, including handling sensitive personal data Integrating with cloud platforms or partner ecosystems such as AWS, Google Cloud and Azure Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. 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 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Задачи: — Разработка многолетней стратегии мощности. — Руководство решениями по инвестициям в инфраструктуру. Требования: — Опыт в планировании мощности и стратегии инфраструктуры. — Навыки работы с Excel и Google Sheets. Условия: — Работа в офисе в Сан-Франциско, Калифорния, США. — Годовая зарплата от 230000 до 280000 USD.

Location: San Francisco Bay Area, USA Workplace: Hybrid Why work at Higgsfield AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. About the role: Higgsfield AI is looking for a highly technical, hands-on MTS, ML Security to join Higgsfield Security and own security across our GPU clusters and AI/ML infrastructure, from model training to inference and production deployment. In this role, you will work as part of the Security team and closely with our ML and Infrastructure teams to design, implement, and operate security controls that protect models, data, and underlying infrastructure. Your core responsibilities will include securing GPU compute environments, assessing infrastructure and AI/ML vendors, and enforcing security requirements through technical controls, deployment policies, and verified remediation. We're looking for someone who combines deep security engineering expertise with a practical, solutions-oriented mindset. The ideal candidate is comfortable working across cloud environments, Kubernetes, Linux, and GPU infrastructure, and understands how to balance security, performance, and reliability in a fast-moving AI environment. This role carries direct ownership of GPU infrastructure security and the security requirements that third-party providers must meet to support Higgsfield’s workloads and data. What you'll do: AI/ML & GPU Infrastructure Security - Own the security of GPU clusters supporting distributed training and production inference across cloud and rented datacenter environments. - Harden GPU hosts, operating systems, drivers, container runtimes, Kubernetes clusters, and workload scheduling configurations; reduce privileged access and unnecessary exposure. - Secure distributed training environments and GPU workloads through isolation, access controls, and data movement restrictions. Validate isolation between tenants and workloads across compute, networking, and storage, including shared GPU environments where applicable. - Design and implement controls to protect sensitive datasets, model checkpoints, weights, and customer data. - Strengthen inference security through tenant isolation, service authorization, secure model loading. - Partner with ML and Platform Engineering teams to integrate security into infrastructure design and development workflows. Vendor Security Assessment & Enforcement - Lead technical security assessments of GPU infrastructure providers, datacenter operators, and other AI security vendors that process Higgsfield data and support AI workloads. - Evaluate vendor architecture and evidence covering tenant isolation, privileged access, data handling and retention, use of customer data for model training, encryption, vulnerability management, and incident response. - Translate security requirements into enforceable technical controls, including approved configurations, and continuous checks for configuration drift. - Track internal and vendor security findings to closure with accountable owners and deadlines, validate remediation, and escalate unmet requirements. Document any approved exceptions with compensating controls and expiration dates. Cloud & Platform Security - Design, implement, and maintain security controls across Linux, Kubernetes, cloud infrastructure, networks, and third party datacenter environments. - Secure infrastructure provisioning, configuration management, and access to third-party infrastructure providers. Restrict and audit vendor and administrator access to cluster management interfaces and production systems. - Implement least-privilege access, workload identity, secrets management, encryption, and auditable access controls. - Identify and remediate vulnerabilities and configuration risks across production systems, including GPU hosts, drivers, and container runtimes, coordinating changes with infrastructure owners to maintain service reliability. Security Operations & Risk Management - Develop and maintain detection and response capabilities for infrastructure and AI-specific security threats, including unauthorized GPU workloads, privilege escalation, and suspicious data transfers. - Investigate and respond to potential credential compromise, unauthorized data access, model theft, and compromised workloads. - Partner cross-functionally to implement practical security improvements that account for the performance, scalability, and reliability requirements of GPU workloads. Requirements: - Strong hands-on experience in Security Engineering, Infrastructure Security, Platform Security, or a related technical discipline. - Deep understanding of Linux, Kubernetes, networking, and cloud infrastructure security. - Practical experience securing or operating GPU clusters or distributed AI/ML infrastructure, with an understanding of training and inference workloads, GPU drivers and runtimes, and workload isolation. - Experience designing and implementing security controls across complex, distributed production environments. - Strong knowledge of identity and access management, workload isolation, encryption, secrets management, and least-privilege principles. - Experience conducting technical vendor security assessments, evaluating supporting evidence, and driving remediation with external providers. - Ability to identify, investigate, and remediate security vulnerabilities and infrastructure threats. - Proficiency in scripting or programming languages such as Python, Go, or Bash. - Experience partnering with Infrastructure, Platform, or ML Engineering teams to implement security solutions. - Strong technical ownership, sound judgment, and the ability to prioritize security risks in a fast-paced environment. - A hands-on, collaborative approach with the ability to independently drive security initiatives from design through deployment, verify that controls work in production, and hold internal teams and vendors accountable for agreed security requirements. Compensation & Benefits - We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth. - Base Salary: The anticipated salary range for this role is $200,000 - $300,000, depending on experience, skills, scope, and location. • Bonus: This role is Bonus eligible and may participate in the Company's discretionary annual bonus program. - Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. - Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks. - The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team. - Significant ownership, direct impact, and opportunities for professional growth as the company scales. This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams. Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.

Location: United States Workplace: Remote Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. We’re looking for a Staff Data Engineer who can take ownership of and drive key initiatives across Data Platform Engineering, including the data lake, event instrumentation, data quality, and data governance. ABOUT THE ROLE: - Location: Remote-first (United States) - Full-time - Permanent - Exempt - The cash compensation for this role is tailored to align with the cost of labor in different geographic markets. We've structured the base pay ranges for this role into zones for our geographic markets, and the specific base pay within the range will be determined by the candidate’s geographic location, job-related experience, knowledge, qualifications, and skills. - United States  (all figures cited below are in USD and pertain to workers in the United States) - Zone A: $212,500 - $255,000 - Zone B: $200,000 - $240,000 - Zone C: $186,500 - $224,000 This role is also eligible to participate in Webflow's company-wide bonus program. Target amounts are a percentage of base salary and vary by career level. Payouts are based on company performance against established financial and operational goals.  Please visit our Careers page https://webflow.com/careers#pay-zones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. - Application Information: - Application deadline: applications accepted on an ongoing basis until position is closed and filled - This posting is for an existing vacancy - Reporting to the Manager, Data Engineering As a Staff Data Engineer, you'll… - Design data solutions across batch, streaming, and real-time workloads. - Design and build reliable data pipelines using Spark, Kafka, Iceberg, and Airflow/MWAA. - Contribute to the evolution of data lake and data platform, including ingestion, processing, storage, and serving patterns. - Build, maintain and scale cloud data infrastructure that includes Kafka, Airflow, Druid, EMR on EKS with reliability and observability in mind. - Implement and improve data quality, observability, reliability, and governance across data pipelines and systems. - Define and improve standards for event instrumentation and governance, including event schemas, validation, and schema evolution. - Build platform solutions for centralized PII handling, data retention, deletion, and residency to support GDPR and CCPA requirements. - Build agent harness capabilities that encode data engineering standards, pipeline patterns, and quality gates into AI tools, enabling agents to safely generate, review, and operate on data platform code. - Contribute hands-on to complex technical initiatives, troubleshoot production issues, mentor engineers, and collaborate with Analytics Engineering and other teams. - Build agent harnesses that embed data engineering standards, pipeline patterns, and quality gates into AI-assisted development workflows. ABOUT YOU: Requirements: - BA/BS degree or equivalent experience - 5+ years of experience in data engineering, building and operating production data pipelines and platforms. - Strong experience with Spark and distributed data processing, including designing and optimizing production data pipelines. - Experience designing batch, real-time, and streaming data solutions using technologies such as Kafka, Spark Structured Streaming, and CDC. - Experience implementing data quality, observability, and reliability across production data systems. - Experience with cloud data infrastructure, CI/CD, and infrastructure-as-code. - Demonstrated experience leading complex data engineering initiatives end-to-end, from technical design and decomposition through implementation and production. - Strong Programming and SQL skills, with experience building reliable and maintainable data systems. You’ll thrive as a Staff Data Engineer if you: - Can navigate ambiguous problems, evaluate architectural tradeoffs, and make pragmatic technical decisions. - Think beyond individual pipelines and consider the end-to-end data ecosystem, from data producers through downstream consumers. - Bring experience with data governance and privacy, including PII management, retention, deletion, data residency, GDPR, or CCPA. - Bring experience with event instrumentation and governance, including event schemas, validation, and schema evolution. - Collaborate with engineers on complex technical problems and help establish practical engineering best practices. - Embrace AI and emerging technologies, applying them in your development workflow and helping the team adopt new tools through shared learnings and best practices. - Stay curious and open to growth  demonstrating a proactive embrace of AI, and actively building and applying fluency in emerging technologies to elevate how we work, drive faster outcomes, and expand collective impact. OUR CORE BEHAVIORS - Build lasting customer trust. We build trust by taking action that puts customer trust first. - Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act. - Reinvent ourselves. We don't just improve what exists, we imagine what's possible. - Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.   BENEFITS - Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company. - Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums. - Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions. - Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired. - Wellness for the whole you. Access to mental health resources, therapy and coaching. - Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally. - Stipends to support our distributed team. Localized support for cell, Wi-Fi, and WFH expenses to help you settle into your best remote life. - Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.   Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.   BE YOU, WITH US At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.   STAY CONNECTED Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.   PLEASE NOTE: We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for accommodation requests will be administered. To join Webflow, you'll need a valid right to work authorization depending on the country of employment. If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes. Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-privacy-notice.