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Data Center Controls Engineer
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 is seeking an experienced Datacenter Controls Engineer to join our Datacenter Infrastructure team. In this role, you will design, implement, and optimize control systems that support our global datacenter infrastructure, enabling the reliable operation of AI at scale. You will work on cutting-edge control systems managing critical datacenter operations including liquid cooling systems (CDUs/CDMs), HVAC, electrical power monitoring systems, and building automation systems. This position requires both technical depth in industrial automation and the ability to collaborate across disciplines to deliver integrated solutions for high-density AI compute infrastructure. Responsibilities System Architecture & Integration - Design and implement multi-site controls architecture across Anthropic's global datacenter facilities - Define network topology, redundancy, and high-availability requirements for control nodes and servers - Develop and maintain standardized frameworks for BACnet, Modbus TCP/IP, OPC-UA, MQTT, and SNMP communication layers - Ensure integration between control systems and enterprise networks while maintaining security boundaries and compliance with cybersecurity frameworks for industrial control systems Control System Design & Implementation - Define, design, develop, and implement control systems for datacenter mechanical, electrical, and building management systems with focus on AI compute environments - Develop SCADA/BMS applications using platforms including Ignition, Niagara/Tridium, or similar HMI/supervisory systems - Select and specify instrumentation including sensors, transmitters, actuators, and control valves for liquid cooling loops, power distribution, and environmental monitoring Data Collection & Visualization - Architect and supervise deployment of centralized telemetry systems capable of storing high-resolution time-series data from power, thermal, and environmental sensors - Develop intuitive dashboards and visualization layers using Ignition SCADA, Grafana, or comparable frameworks for facilities, operations, and engineering teams - Leverage control systems to enable performance insights, fault detection, and predictive maintenance capabilities Construction Integration & Documentation - Participate in new design and construction projects to ensure controls and BMS standards are embedded from design through commissioning - Define and review controls and instrumentation specifications in architectural and MEP packages - Create comprehensive technical documentation including P&IDs, control narratives, sequence of operations, and commissioning procedures - Validate installed systems during commissioning for proper network configuration, protocol compatibility, and data visibility Minimum Qualifications - Bachelor's degree in Engineering (Electrical, Controls, Mechanical, Computer) or equivalent practical experience - 7+ years of experience in control systems design and implementation for industrial automation, building automation, or datacenter systems - Deep familiarity with industrial communication protocols: BACnet, Modbus TCP/IP, OPC-UA, MQTT, SNMP, Ethernet-IP - Experience with instrumentation selection, control panel design, and control system integration - Working knowledge of network architecture including subnets, VLANs, firewall rules, and IP management - Strong documentation skills and ability to work effectively in cross-functional teams Preferred Qualifications - 10+ years in datacenter, critical facilities, or mission-critical infrastructure environments - Experience with liquid cooling systems including CDUs, CDMs, and cooling tower control systems - Background in high-density rack integration environments and AI/ML compute infrastructure - Experience designing or deploying BMS/SCADA systems such as Ignition, Niagara/Tridium, Wonderware, or similar - Strong background in database integration (SQL Server, InfluxDB, PostgreSQL, TimescaleDB) and data logging architecture - Proficiency in Python or scripting for automation/configuration within SCADA/BMS frameworks - Experience deploying multi-site redundant controls servers with high-availability requirements - Professional Engineering (PE) license or vendor certifications (Schneider, Rockwell, Siemens) - Knowledge of relevant codes and standards: ASHRAE, NFPA, IEEE, ISA - Familiarity with Grafana, Node-RED, Ignition Perspective, or equivalent visualization tools - Experience bridging cloud orchestration systems with facility-level power controls and load management (e.g., DCIM, BMS, EPMS) 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: $320,000 - $405,000 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.
Software Engineer, Public Sector - New Grad
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Public Sector engineers build the core product including the systems required to ingest and process federal datasets that support real-time decision-making in contested environments. As a New Grad Software Engineer on this team, you will own meaningful, mission-facing work from day one: shipping features, sitting with the government stakeholders who use them, and iterating fast. Example Projects - Build multi-layered guardrails that keep agents safe and predictable in high-stakes federal environments - Optimize data retrieval for agents, including RAG pipelines over large, heterogeneous federal datasets - Build orchestration for fleets of asynchronous agents running long-horizon tasks - Develop systems that automatically alert users to deviations and anomalies in incoming data - Create interfaces that illustrate how an agent reached a decision, so operators can audit and trust its output - Develop data pipelines and ML infrastructure that make previously siloed government data sources accessible to agents - Build evaluation infrastructure that measures model reliability against mission requirements - Ship full-stack tooling that lets analysts query, visualize, and explore mission data - Deploy and harden applications into secure, air-gapped, and cloud-native government environments Requirements - A graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) - Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services, talking to users, figuring out 'what' to build and then iterating - Previous Product/Software Engineering internship experience - Track record of shipping high-quality products and features at scale - Experience building systems that process large volumes of data - Experience with Python, Typescript, React, and/or MongoDB - Strong written and verbal communication — you will work directly with government stakeholders and must be able to explain technical concepts to non-technical audiences - Comfort with ambiguity and evolving requirements, and a willingness to learn new domains quickly Nice to Have - Hands-on experience with LLMs, evaluations, or agentic systems — whether from internships, research, or personal projects - Familiarity with cloud platforms (AWS, Azure, GCP), containerization (Docker), and orchestration (Kubernetes) - Exposure to ETL, data modeling, data warehousing, or data governance - Prior experience with, or demonstrated interest in, national security, defense, or civil government technology - Open source contributions or a portfolio of shipped side projects How We Work Our credos shape how we make decisions and work as a team: - Earn Customer Love — trust is earned with every interaction, every delivery, and every problem we solve - Team Flow — ideas, energy, and support move freely across teams; optimize for the whole - Quality is Our Cheat Code — the systems that deliver quality consistently are a structural advantage - Find the 20% — find the inputs that drive the outcomes and execute them completely - Write the Market — our research puts us at the frontier, and we bring our partners there first - Three Moves Ahead — consider the consequences of consequences, and plan accordingly Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $124,000 - $162,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Staff+ Software Engineer, Account Creation
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 looking for software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies. Responsibilities: - Develop monitoring systems to detect unwanted behaviors from our API partners and potentially take automated enforcement actions; surface these in internal dashboards to analysts for manual review - Build abuse detection mechanisms and infrastructure - Surface abuse patterns to our research teams to harden models at the training stage - Build robust and reliable multi-layered defenses for real-time improvement of safety mechanisms that work at scale You may be a good fit if you have: - A Bachelor’s degree in Computer Science, Software Engineering or comparable experience - Proficiency in Python and Typescript - An ability to work across the stack - Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Strong candidates may also: - 8+ years of experience in a software engineering position - Have experience with integrity, spam, fraud, or abuse detection and mitigation - Have experience building trust and safety detection mechanisms and intervention for AI/ML systems - Have experience with prompt engineering, jailbreak attacks, and other adversarial inputs - Have worked closely with operational teams to build custom internal tooling 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: $320,000 - $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. 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.
Senior Developer Advocate, AI Content & Community
SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. SambaNova is hiring a Senior Developer Advocate, AI Content & Community to make its technology visible, useful, and compelling to AI builders. This role will combine hands-on development with the reach and instincts of a trusted creator: building standout demos, showing developers what is possible, and working with influential voices across the developer ecosystem to amplify SambaNova’s technology. About the Role This is a builder-and-influencer role centered on working demos and developer credibility. You will use SambaCloud and the broader SambaNova platform to create agentic AI demos, applications, code, tutorials, videos, and live experiences that developers want to try and share. You will also cultivate relationships with technical creators, open-source contributors, community leaders, and developer influencers, turning product capabilities and ecosystem integrations into credible moments of discovery. The right candidate can prototype quickly, explain the technology clearly, perform naturally on camera or onstage, and convert one strong demo into content that travels across repositories, social channels, livestreams, workshops, and events. Responsibilities - Build polished agentic AI applications, reference demos, and repeatable developer workflows that showcase what developers can create with SambaCloud - Own a steady demo pipeline from concept and prototype through testing, packaging, documentation, recording, live delivery, and reuse by the field and community - Create original developer content across code repositories, videos, livestreams, tutorials, blog posts, social posts, and other developer-native formats - Serve as an authentic public voice for SambaNova across GitHub, YouTube, X, LinkedIn, community forums, meetups, hackathons, and conferences - Develop relationships with developer influencers, technical creators, open-source maintainers, and community leaders who can extend the reach and credibility of SambaNova’s work - Co-create demos, technical content, events, and social moments with creators and ecosystem partners - Translate inference, model serving, agent workflows, and platform capabilities into practical examples without sacrificing technical substance - Turn product launches, integrations, benchmarks, and technical proof points into compelling demos and developer stories - Engage directly with developers, answer questions, gather feedback, and bring recurring friction and feature requests back to Product and Engineering - Partner with Developer Relations, Product, Engineering, Product Marketing, Design, and Partner teams to align demos and content with priority use cases and launches - Measure demo usage, developer activation, creator participation, social reach, engagement, community growth, and qualitative feedback; use those insights to improve the program What We’re Looking For - 5+ years of experience in developer advocacy, software engineering, technical content creation, developer marketing, or a combination of these disciplines - Hands-on experience building with Python, APIs, large language models, and contemporary agent or orchestration frameworks - A substantial public portfolio of working demos, repositories, tutorials, talks, videos, livestreams, or substantive social content - A demonstrated ability to earn attention and engage a technical audience through developer communities and social platforms - Strong on-camera, live presentation, writing, and technical storytelling skills - Fluency in the AI developer ecosystem and genuine curiosity about new models, agent patterns, tools, and infrastructure tradeoffs - Ability to prototype quickly, troubleshoot live demos, learn in public, and respond constructively to technical feedback - Comfort owning an editorial and demo calendar and shipping consistently in a fast-moving environment Preferred Qualifications - Experience creating agentic AI demos, multimodal applications, or production-oriented reference implementations - Familiarity with OpenAI-compatible APIs, model evaluation, prompt caching, retrieval, tool use, and inference performance concepts - An established network or engaged presence among AI developers, technical creators, open-source projects, or developer communities - A track record of successful collaborations with developer influencers, technology partners, creators, or open-source maintainers - Experience hosting workshops, hackathons, meetups, panels, livestreams, or conference sessions - Video production or editing skills and an instinct for adapting one technical demo to multiple channels without turning it into hype Why This Role Matters Developers trust working code, useful demos, and respected voices more than claims. This role will make SambaNova tangible to builders, create demonstrations that prove what the platform can do, and mobilize the developer influencers and communities that can carry those stories across the AI ecosystem. Base Salary Range: Base Pay Range $196,000 - $240,000 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.
Applied AI Engineer, Codex
About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software. We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex. About the Role As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environments, security, reliability, evaluation, and operational readiness, while ensuring deployments translate into measurable improvements in engineering productivity and software delivery. You will work closely with OpenAI Product, Research, Engineering, Security, Sales, and the broader Codex organization, translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems, sustained developer adoption, and meaningful improvements to how engineering organizations build software—not simply successful demonstrations or enablement activity. This role is based in our Madrid office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Partner directly with engineering leaders and hands-on developers to identify high-value opportunities for Codex and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. - Design, build, and deploy AI-powered software development workflows that improve how engineering teams plan, write, test, review, debug, and deliver software. - Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators—often using Codex as part of your own development process. - Help customers progress from promising experiments to reliable production workflows, sustained developer adoption, and scaled impact across engineering organizations. - Design systematic approaches for evaluating AI coding systems using representative software engineering tasks, automated graders, production signals, and developer feedback. - Make sound technical decisions across models, agents, tools, developer environments, integrations, reliability, observability, latency, cost, safety, security, and operational readiness. - Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive technical blockers toward resolution. - Lead technical deep dives, workshops, and hands-on enablement that help engineering teams understand and adopt advanced AI coding workflows effectively and safely. - Gather high-fidelity insights from real-world Codex deployments and translate them into clear product proposals, model feedback, and technical requirements for OpenAI Product, Research, and Engineering teams. - Create reusable architectures, tooling, examples, guides, and technical patterns—including contributions to resources such as the OpenAI Cookbook—that accelerate future Codex deployments. - Influence customer engineering strategy by helping technical leaders understand how AI coding systems can reshape their software development lifecycle, engineering practices, and organizational workflows. You’ll thrive in this role if you: - Have a demonstrated track record of designing, building, and delivering software or AI systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, developer tooling, customer engineering, solutions architecture, or technical consulting. - Can point to substantial personal contributions in code, architecture, evaluation, debugging, integrations, or production engineering—not only program, enablement, or stakeholder management. - Are highly proficient in Python and comfortable working across modern software development environments; experience with JavaScript, TypeScript, or another relevant language is valuable. - Are an active user of AI coding tools and have developed a strong point of view on how AI can improve developer productivity and software engineering workflows. - Enjoy building high-signal prototypes, integrations, automations, and production solutions that demonstrate and deliver what AI coding systems can enable. - Understand how to evaluate AI coding systems systematically, including designing representative tasks, automated evaluations, production signals, and mechanisms for incorporating developer feedback. - Have navigated enterprise production requirements such as developer tooling integrations, reliability, observability, security, privacy, data governance, performance, and cost. - Can connect technical decisions to developer workflows, adoption, engineering productivity, and measurable business outcomes. - Communicate with clarity and credibility across hands-on engineers, engineering leaders, security teams, product leaders, and executives. - Are comfortable leading technical workshops and hands-on sessions that help engineering organizations adopt new development workflows and technologies. - Bring high agency, strong technical judgment, and end-to-end ownership in ambiguous and rapidly evolving environments. - Learn quickly, challenge assumptions constructively, and collaborate with humility; deep prior experience with OpenAI products is not required. - Are able to speak English and Spanish fluently. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Applied AI Architect, Startups
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 As a Solutions Architect on the Startups Applied AI team at Anthropic, you will win the trust of founders and engineers by being an exceptional technical partner, helping startups successfully build on the Claude Developer Platform as they grow from early product to scale. You'll combine deep technical expertise with a builder-first mindset to help startups architect innovative LLM solutions, win technical evaluations, and get the most out of Claude. Working closely with Account Executives and the broader Sales, Product, and Engineering teams, you'll guide startups from initial technical discovery through successful deployment and beyond. You'll leverage your expertise to help founders understand Claude's capabilities, develop evals, and design architectures that maximize the value of our AI systems. Responsibilities: - Partner with Account Executives to deeply understand startup requirements, translate them into technical solutions, and serve as a trusted technical advisor throughout the Claude adoption journey from initial evaluation through deployment and expansion - Win technical evaluations that demonstrate why Claude is the best foundation for what startups are building, helping them develop evaluation frameworks to measure Claude's performance for their specific use cases - Build technical credibility with founders, founding engineers, and startup engineering teams by speaking their language, understanding their build patterns, and guiding technical architecture decisions - Gather insights on how startups are building with Claude, identify emerging use cases and deployment patterns, and deliver feedback to Product and Engineering teams - Travel to customer sites, startup-focused events, and industry conferences for workshops, technical deep dives, and relationship building You may be a good fit if you have: - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, Forward Deployed Engineer, or technical founder who has done founder-led sales - Experience working with startups or high-growth technology companies; you understand the velocity and constraints of early-stage companies - Strong builder credibility through experience as a software engineer or technical founder; you speak the language of builders and have the presence to earn the trust of technical founders and startup engineering teams - Deep technical proficiency with building and scaling AI products, a pulse on AI engineering best practices, and the ability to demonstrate why Claude is the best foundation - Hands-on experience building and deploying LLM-powered applications in production, with expertise in context engineering, evaluation frameworks, and modern AI architectures - Strong technical communication skills with the ability to translate complex AI concepts into actionable insights for founders and engineering teams - Track record of selling technical products in competitive markets - Comfortable with Python and familiarity with common LLM frameworks, tools, and integration patterns - Passion for making powerful technology safe and societally beneficial 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: £165,000 - £190,000 GBP 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.
Applied AI Engineer, Startups
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 As an Applied AI Engineer at Anthropic, you will be a trusted technical advisor helping tech-forward companies build on the Claude Developer Platform as they grow and scale. You'll lead deep technical engagements, partnering directly with engineering teams to help them develop their products on top of Claude - advising on implementation, agent design, and working alongside them to build at the frontier of AI. Working closely with Applied AI Architects, Account Executives, and Anthropic's Product and Engineering teams, you'll guide customers through deep technical engagements. You'll leverage your AI engineering expertise to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable tech-forward businesses to succeed with Claude. Responsibilities - Serve as a deep technical advisor to high-growth, tech-forward companies, working alongside them to build innovative use cases that push the boundaries of AI - Work hands-on with customer engineering teams: pair programming, architecture reviews, and code contributions that accelerate their development - Develop prototypes and technical documentation—including evaluation suites, AI engineering techniques, and architecture diagrams—that enable customers to build and scale with Claude - Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements - Identify patterns across engagements and contribute insights back to Product, Engineering, and the broader Applied AI team - Create technical content for developer audiences including documentation, tutorials, and sample code - Foster community engagement through hackathons, webinars, technical office hours, and developer-focused events - Travel to customer sites for workshops, implementation support, and relationship building You may be a good fit if you have - 4+ years of experience as a Software Engineer, Forward Deployed Engineer, or technical founder - Experience in a customer-facing or pre-sales technical role - partnering with customers to scope, design, and deliver solutions - Production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale - Strong programming skills with proficiency in Python and experience building production applications - Experience working with high-growth, tech-forward companies - Ability to context-switch across industries (healthcare, fintech, etc.) and use cases - Builder credibility that earns trust with technical founders and engineering leaders - you've shipped products and can speak from experience - Strong technical communication skills with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans - Experience facilitating technical workshops, hackathons, or developer-focused events - Passion for making powerful technology safe and beneficial 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: £225,000 - £255,000 GBP 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.
Applied AI Architect, Public Sector
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: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping systems integrators, startups, and other GovTech companies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with Claude Code, the Claude API, and Claude for Enterprise - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel frequently to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - US Secret Clearance preferred for working with defense tech customers - Prior work in government, government contracting, or government tech preferred - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Familiar with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems 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: $240,000 - $315,000 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.
Staff Software Engineer - AI Compute, Together Clo...
About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the Together GPU Clusters flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. This is an architect-and-build role. Fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes — you'll set the architecture for these across our global and in-DC services, and be a key owner of the hardest parts, in the code as well as the design. Your designs will span the IaaS layer of a greenfield Vera Rubin data center up to the global management plane that schedules capacity across all of them. At this level the job is as much leverage as code: the standards you set and the engineers you grow decide how fast the rest of Together Cloud ships. Responsibilities - Own the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that keeps GPU compute and DC networking high-performance, portable, and strongly isolated across heterogeneous hardware. - Own the in-DC IaaS layer: architect and roadmap the services, Kubernetes operators, and libraries that provision and manage compute, storage, and networks in our data centers — VMs, parallel filesystems, VPCs, and InfiniBand partitions; lead its build-out for a new Vera Rubin data center with thousands of GPUs, from hardware bring-up to customer-facing API. - Design the GPU scheduling and global management plane: the distributed control plane behind on-demand and reserved clusters across dozens of data centers, including the systems that scale per-cluster limits and automate the onboarding of new capacity. - Architect monitoring and automated remediation for fault tolerance: the strategy for automated detection, isolation, and recovery of failed nodes that keeps distributed pretraining and large-scale inference running through hardware failures. - Set technical direction across teams: lead design reviews, resolve cross-cutting architectural disagreements, unblock cross-team dependencies and integration risks, and define the standards other engineers build against — measured in cluster reliability, time-to-first-GPU on new capacity, and quality at scale. - Grow the team: mentor senior and junior engineers, deepen the team's expertise in virtualization, DC networking, and GPU infrastructure, and help raise the hiring bar for Together Cloud. - Set the engineering bar: create the testing frameworks, tools, and developer documentation that make our systems robust and usable by other teams, and shape the core, open-source Together AI platform. To be successful you'll need to be deeply technical and an excellent communicator — expert software development fundamentals, deep systems knowledge and troubleshooting instincts, and the leadership and diplomacy skills to align teams that don't report to you. Much of this work starts ambiguous, and we expect you to define the scope yourself and drive it to production. Requirements - 7+ years of professional software development experience, with expert-level proficiency in at least one backend language (Golang desired), writing high-performance, well-tested, production-quality code. - Track record of owning the architecture of large distributed systems from blank page to production at scale, including the judgment calls that could not be reversed cheaply. - Deep experience building and operating globally distributed, high-performance microservice architectures across one or more cloud providers (AWS, Azure, GCP). - Expert systems knowledge across compute, networking, and storage — including concurrency, memory management, performant I/O, and scale at a global level. - Demonstrated technical leadership beyond your own commits: mentoring senior engineers, leading design reviews, and driving alignment across teams that do not report to you. - Excellent communication and diplomacy skills — able to write design docs that settle arguments, and to work effectively with technical and non-technical stakeholders. - Experience building and operating reliable, customer-facing production systems at scale, and owning the infrastructure automation (Terraform, Ansible), observability (Prometheus, Grafana), and CI/CD (GitHub Actions, ArgoCD) that keep them healthy. Preferred Qualifications (not must haves) - Deep Kubernetes internals experience, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches to Kubernetes itself - Deep experience with VMs/hypervisors, such as QEMU/KVM, cloud-hypervisor, VFIO, virtio, PCIE passthrough, Kubevirt, SR-IOV - Deep experience with DC networking tech + solutions, such as VLAN, VXLAN, VPN, VPC, OVS/OVN - Experience with Cluster API or similar - Experience working on high-performance compute, networking, and/or storage - Experience virtualizing GPUs and/or InfiniBand - Experience building IaaS or PaaS systems at scale - Experience with DPUs/SmartNICs - GPU programming, NCCL, CUDA knowledge About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $260,000 - $300,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy
Applied AI - Forward Deployed Engineer - Defense
ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB The Applied AI for Defense team is Mistral’s specialized unit dedicated to delivering high-impact, secure AI solutions for institutions and organizations operating in highly regulated and strategic environments. We work hand-in-hand with clients to design, deploy, and maintain AI systems that meet the highest standards of reliability, security, and operational excellence. Our team combines deep technical expertise with a rigorous approach to compliance and risk management, ensuring that every solution is both cutting-edge and fully aligned with the unique constraints of our partners. Mistral AI is seeking an Applied AI Engineer to join this team. You will be responsible for the technical design, implementation, and deployment of AI solutions tailored to the needs of critical infrastructure and sovereign institutions. Your work will directly contribute to projects with significant societal and operational impact. WHAT YOU WILL DO • Individually deploy AI solutions into production for use cases with significant operational and strategic impact. • Develop state-of-the-art GenAI applications tailored to the specific needs of sovereign institutions and critical infrastructure, driving technological transformation in collaboration with our customers. • Work closely with our researchers, AI engineers, and product teams on complex customer projects involving advanced fine-tuning, LLM applications, and contributions to our open-source codebases for inference and fine-tuning. • Participate in pre-sales discussions to understand the needs, challenges, and aspirations of potential clients, providing technical guidance on Mistral’s products and technologies to diverse stakeholders. • Collaborate with our product and science teams to continuously improve our offerings based on customer feedback, with a focus on security, compliance, and performance. HOW WE WORK IN APPLIED AI • We care about people and outputs. • What matters is what you ship, not the time you spend on it • Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. • Always ask why. The best solutions come from deep understanding, not from copying what worked before • We say what we mean. Feedback is direct, timely, and given because we care. • No politics. Low ego, high standards. • We embrace an unstructured environment and find joy in it. ABOUT YOU • Fluent in English. • PhD or Master's in AI, Machine Learning, Computer Science, or related field. • 2+ years of experience in AI/ML • Proven track record of leading teams to deliver complex AI projects from prototyping to production. • Deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale. • Proficient in Python, PyTorch, and modern AI frameworks (LangChain, HuggingFace). Cloud platforms (AWS, GCP, Azure) and MLOps tools a plus. • Strong software engineering skills: API design, backend/full-stack development, system architecture. • Excels in technical communication with technical and non-technical audiences, including executives. • Thrives in fast-paced collaborative environments and is passionate about mentoring technical talent. IT WOULD BE GREAT IF YOU • Have experience with React or other frontend frameworks. • Have experience with Deep Learning in PyTorch • Contributed to open-source projects in the LLM or AI space. • Have experience in customer-facing roles with a focus on enterprise AI adoption. SECURITY & COMPLIANCE CRITERIA • Eligibility: must hold citizenship in the target territory (France for now). • Clearable: must meet all local requirements for high-level security clearance (e.g., no criminal record, fulfillment of national service obligations). WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Research Engineer, Machine Learning (Reinforcement...
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 teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation. Representative projects: - Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters. Help scale our systems to handle increasingly complex research workflows. - Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents which push the state of the art for the next generation of models. - Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows. - Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research. You may be a good fit if you: - Are proficient in Python and async/concurrent programming with frameworks like Trio - Have experience with machine learning frameworks (PyTorch, TensorFlow, JAX) - Have industry experience in machine learning research - Can balance research exploration with engineering implementation<
Data Platform Engineer
Who We Are 2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO). Founded in 2005, 2K Games is a global video game company, publishing titles developed by some of the most influential game development studios in the world. Our studios responsible for developing 2K’s portfolio of world-class games across multiple platforms, include Visual Concepts, Firaxis, Hangar 13, CatDaddy, Cloud Chamber, 31st Union, HB Studios, and 2K SportsLab. Our portfolio of titles is expanding due to our global strategic plan, building and acquiring exciting studios whose content continues to inspire all of us! 2K publishes titles in today’s most popular gaming genres, including sports, shooters, action, role-playing, strategy, casual, and family entertainment. Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K’s portfolio currently includes several AAA, sports and entertainment brands, including global powerhouse NBA®️ 2K, renowned BioShock®️, Borderlands®️, Mafia, Sid Meier’s Civilization®️ and XCOM®️ brands; popular WWE®️ 2K and WWE®️ SuperCard franchises, TopSpin 2K25, as well as the critically and commercially acclaimed PGA TOUR®️ 2K At 2K, we pride ourselves on creating an inclusive work environment, which means encouraging our teams to Come as You Are and do your best work! We encourage ALL applicants to explore our global positions, even if they don’t meet every requirement for the role. If you're interested in the job and think you have what it takes to work at 2K, we encourage you to apply! What We Need The Data Platform Engineer is responsible for designing and evolving the core architectural foundation of 2K’s data ecosystem. While Data Engineers build pipelines and DataOps Engineers manage reliability, the Data Platform Engineer focuses on building the underlying platforms—including Snowflake, Databricks, Kafka, and internal frameworks—that enable self-service data capabilities across the organization. this role ensures high-performance environment scalability for billions of global player events and creates seamless interoperability between complex data systems. What You Will Do - Platform Architecture & Development: Lead the design, implementation, and optimization of core data platform components, including Snowflake, Databricks, and AWS S3 Data Lakes. - Streaming Infrastructure: Manage and scale high-throughput streaming systems using Kafka or Kinesis to support real-time game telemetry and low-latency analytics. - Self-Service Enablement: Develop "Data-as-a-Service" (DaaS) features that allow Business Units and Studios to onboard data and manage access with minimal friction. - Distributed Systems Optimization: Optimize Spark and PySpark applications for performance and cost-efficiency across large-scale distributed clusters. - Security & RBAC Architecture: Design and automate granular access control models to ensure data security and compliance with global regulations (e.g., GDPR, CCPA). - Interoperability & Standards: Ensure seamless data flow and interoperability between disparate platforms (utilizing technologies like Apache Iceberg) to maintain a Single Source of Truth (SSOT). - Technical Leadership: Serve as a subject matter expert for the data platform, translating complex business needs into sca
Host Systems Software Engineer
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for an experienced systems software engineer to help define and build the host software stack for our custom next-generation AI systems. You will work close to the hardware on performance-critical software, including Linux kernel drivers, high-throughput I/O paths, and system-scale networking and RDMA. This role spans architecture, implementation, platform bring-up, debugging, and performance optimization. You will work across hardware and software boundaries to make new systems usable end to end, from low-level device interfaces through userspace tooling and production validation. In this role you will: - Design, implement, and debug host-side systems software for AI infrastructure, including Linux kernel drivers and supporting userspace components. - Build and optimize software paths for high-throughput, low-latency communication, including RDMA and related networking functionality. - Develop software around PCIe, DMA, NICs, accelerators, memory movement, and device interaction. - Bring up new hardware platforms and diagnose complex issues across kernel, firmware, networking, and hardware boundaries. - Build tooling for integration, testing, diagnostics, observability, qualification, and performance characterization. - Collaborate with hardware, networking, and platform teams to define interfaces and integrate new capabilities. - Work with external vendors where needed to integrate technologies and drive issues to resolution. - Contribute across the systems software stack as the platform and team evolve. - Help shape the technical direction and engineering practices for a growing systems software stack. You might thrive in this role if you have: - Experience building low-level or performance-critical systems software. - Strong programming skills in C or C++, with proficiency using Python and Linux tooling for automation and debugging. - Strong Linux systems fundamentals and the ability to debug across hardware and software boundaries. - Hands-on experience in at least one relevant area, such as Linux kernel drivers, kernel networking, RDMA, PCIe, DMA, NIC software, accelerator software, or high-performance I/O. - Experience owning complex software projects from design through implementation, bring-up, and validation. - Ability to thrive in ambiguity, work across subsystem boundaries, and build systems from scratch. - Strong cross-functional communication skills. Preferred Qualifications - Experience developing Linux kernel drivers or other OS-level performance-critical components. - Familiarity with RDMA or RoCE, ibverbs, kernel networking, or congestion-control concepts such as ECN and DCQCN. - Experience with PCIe, DMA, peer-to-peer communication, SR-IOV, IOMMU, dma-buf, or related accelerator and I/O subsystems. - Experience bringing up accelerators, NICs, SoCs, or custom hardware platforms. - Experience profiling and optimizing high-throughput, low-latency systems. - Familiarity with Rust or experience using Rust for systems programming. To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Machine Learning Engineer, API Multicloud
About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will - Partner with strategic customers and internal teams to define target model behaviors, diagnose failure modes, and translate real-world needs into training, evaluation, and system requirements. - Build and scale production ML systems for model customization, post-training, and fine-tuning-as-a-service workflows. - Design, run, and interpret experiments to see whether training and customization workflows are producing the intended outcomes, and identify changes to data, evaluation, training, or infrastructure that improve performance. - Partner with backend and infrastructure engineers to integrate ML capabilities into AWS-native API environments. - Feed learnings from partner deployments back into the platform by proposing and implementing improvements to post-training systems, tooling, APIs, and developer workflows. - Work closely with Research and Applied teams to bring model improvements, training workflows, and evaluation best practices into production. - Help design systems that allow strategic partners and enterprise customers to safely customize OpenAI models for high-value use cases. - Debug and improve complex systems spanning model behavior, training data, APIs, distributed infrastructure, and customer-facing product surfaces. - Operate with high ownership in a 0→1 environment where requirements are ambiguous, systems are evolving quickly, and reliability matters. Your background might look something like: - Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience. - 3+ years of professional engineering experience in relevant ML, infrastructure, or product-driven engineering roles. - Strong ML engineering experience building, training, fine-tuning, evaluating, or deploying production AI systems, with hands-on experience in deep learning, transformer models, and frameworks like PyTorch or TensorFlow. - Hands-on experience with training and fine-tuning large language models, including methods like supervised fine-tuning, distillation, preference optimization, reinforcement learning, or other post-training techniques. - Strong software engineering fundamentals, including data structures, algorithms, systems design, and high-quality production code in Python, Rust, or similar languages. - Experience with model customization, evaluation systems, data pipelines, distributed systems, cloud infrastructure, or production ML platform tradeoffs. - Ability to operate across model behavior, APIs, and infrastructure, while collaborating closely with Research, Safety, product engineering, infrastructure, and external technical partners. - Comfort moving quickly through ambiguity, owning problems end-to-end, and learning whatever is needed to get the job done. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
AI Systems Engineer, Codex Agents
AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do - Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. - Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. - Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. - Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to improve solve rate, reliability, latency, and cost. - Improve observability, profiling, and diagnostics across the agent stack, from backend systems to inference, GPUs, and fleet capacity. - Work closely with research to make the harness trainable, measurable, and useful for improving frontier agentic models. - Build shared primitives that make Codex faster, safer, more reliable, and easier for other teams and open-source users to build on. You Might Be A Good Fit If You - Have built or operated production systems in distributed systems, infrastructure, developer tooling, sandboxing, virtualization, cloud platforms, or ML systems. - Enjoy working across layers: Rust systems code, Python configuration layers, APIs, agent orchestration, evals, logs/traces, inference behavior, runtime constraints, and user outcomes. - Have hands-on experience with LLM applications, coding agents, evals, model deployment, inference, compiler/runtime performance, or developer platforms. - Care deeply about reliability, safety, performance, debuggability, and clean abstractions. - Can debug from evidence and move quickly from ambiguous production failures to practical, durable fixes. - Want to work close to research while still shipping changes to production - Still write meaningful code, show strong ownership, and can lead scoped or multi-team AI systems work. Bonus Points - Deep Rust, systems, sandboxing, isolation, or low-level platform experience. - Experience with coding agents, agent harnesses, tool-using LLM systems, model evals, or post-training feedback loops. - Background in compilers, kernels, runtimes, inference optimization, GPU systems, benchmarking, profiling, or performance engineering. - Experience building production infrastructure used by many engineers or users under demanding reliability and security constraints. - Open-source infrastructure or developer-platform work with strong taste for APIs and usability. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
AI Infrastructure Engineer, Serving Platform
As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments. The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company. You will: - Build and maintain fault-tolerant, high-performance systems for serving LLMs and other models at scale. - Build an internal platform to empower LLM capability discovery. - Collaborate with researchers and engineers to integrate and optimize models for production and research use cases. - Conduct architecture and design reviews to uphold best practices in system design and scalability. - Develop monitoring and observability solutions to ensure system health and performance. - Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. Ideally you'd have: - 4+ years of experience building large-scale, high-performance backend systems. - Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++). - Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.) - Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc. - Experience with containers and orchestration tools (e.g., Docker, Kubernetes). - Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform). - Proven ability to solve complex problems and work independently in fast-moving environments. Nice to haves: - Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providi
Security Controls Assurance Lead
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 Security Governance, Risk, and Compliance (GRC) team is the connective tissue that holds the company accountable to its security commitments. We translate regulatory, customer, and voluntary obligations into controls that teams act on, and give leadership a bird's-eye view of how well we're meeting them. We're building toward a fundamentally different kind of GRC: one that directs Claude, with the right humans in the loop, to challenge and evidence the performance of controls continuously rather than through periodic audits. We are designing an integrated compliance and risk ecosystem that serves as a trust engine and an independent risk advisor as Anthropic governs itself at a level beyond frameworks. As part of Security GRC's technical controls assurance function, you will be the voice on what the control environment must achieve. You will define control requirements and acceptance criteria for our global compliance obligations (e.g. SOC 2, ISO 27001/42001, HIPAA, public sector) across the software development lifecycle, pair with engineering as they design and implement against those requirements, and validate that what ships actually meets the bar. Key responsibilities - Define the control framework and requirements for autonomous AI operators in collaboration with Security, Internal Audit, and Engineering, including change review and approvals, human-in-the-loop, and evidence collection. Assess implementations against those requirements. - Pressure-test major infrastructure, system, and agent framework changes for control impact during design, before decisions become expensive rework. - Set the compliance bar for home-built systems. Collaborate with teams to define what the internal system must provide from day one, such as auditability, segregation of duties, and change control over the tool itself. - Define the criteria for where and when AI can operate, supplement, or replace a manual process or control, including the human-in-the-loop thresholds and evidence documentation. - Establish the validation, evidence, and governance standards that allow AI-performed and AI-assisted processes and controls to withstand external audit and regulatory scrutiny. - Assess the introduction of new compliance frameworks and changes in scope (new regulations, certifications, products, or entities), providing a sufficient technical and compliance lens on their impact to control design, evidence requirements, and engineering effort before commitments are made. - Stand up or advise on audit workflows for the assurance team, including Claude-driven control testing, automated evidence collection, walkthrough preparation, and framework mapping against our common controls framework, materially raising automated evidence coverage and cutting audit prep time. Minimum qualifications - Thrive at the pace of a hypergrowth company. You’re comfortable making calls with incomplete information and reprioritizing as scope shifts. - Have supported technology control programs through SOX readiness or as a public company or with equivalent rigor (FedRAMP, large mult
Staff Infrastructure Engineer, Cluster Infrastruct...
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 Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world. Key responsibilities - Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning - Partner across teams to ensure new compute capacity is ingested on time - Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity - Collaborate with security owners to ensure clusters are provisioned secure-by-default - Define and drive strategy on cluster scalability, homogeneity and fault tolerance - Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy - Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health - Support the growth of engineers around you through technical mentorship and coaching Minimum qualifications - Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure) - Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform. - Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems - Ability to build alignment across senior stakeholders and communicate effectively at all levels Preferred qualifications - 10+ years of software engineering experience, including time as a technical lead setting direction for a team - Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes) - Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like) - Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield) - Experience with cluster and host networking: CNI (Cilium), eBPF,
Staff+ Software Engineer, Developer Productivity
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 Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale — from the source control and language ecosystems that underpin our monorepo, to the build and CI infrastructure that keeps thousands of daily builds running reliably across multiple cloud providers, to the developer acceleration tooling that deeply integrates Claude into engineering workflows. Team Matching: Team matching is determined after the interview process based on interview performance, interests, and business priorities. Please note we may also consider you for different Infrastructure teams. Responsibilities: - Own the technical strategy and roadmap for your area, translating team-level goals into concrete execution plans - Define infrastructure architecture, ensuring the hardest problems get solved — whether by you directly or by working through others - Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume workloads across all engineering teams - Own and evolve build environments, package management, and dependency systems to enable fast, reproducible builds - Define and implement language ecosystem standards, tooling, and frameworks that drive developer productivity across research and production workloads You may be a good fit if you: - Have deep experience with build systems, CI/CD pipelines, and/or developer tooling in a large monorepo environment - Have strong proficiency in Python, Rust and/or Go - Are obsessed with developer productivity and reducing friction in the software development lifecycle - Have experience with container orchestration and infrastructure at scale - Have excellent communication skills and enjoy supporting internal partners to improve their development experience - Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges Strong candidates may have: - 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure - 3+ years (not including internships or co-ops) of experience leading large scale complex projects or teams as a tech lead - Experience with CI orchestration tools (Buildkite, Jenkins, GitHub Actions, or similar) and merge queue management at scale - Experience building or operating remote build execution systems (B
Staff Software Engineer, iOS
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 looking for seasoned iOS engineers to join our Claude mobile product team and help build apps that harness the transformative power of advanced language models. Our mission is to unlock the potential of advanced AI through elegant, user-friendly mobile applications that put unprecedented capabilities at users' fingertips. You will work with a talented team of engineers, researchers, design and Product teams to design and implement key components of our products. Join us in this exciting mission to transform how people engage with technology and unlock new realms of human potential. Key r esponsibilities - Architect and implement cutting-edge iOS applications - Develop novel solutions leveraging AI technologies - Optimize performance at all levels of the mobile stack - Champion best practices in mobile development - Obsessive attention to detail and app experience - Contribute to backend systems as needed Minimum qualifications - Expertise in Swift, UIKit, SwiftUI, and iOS frameworks - Proficiency with the latest mobile platform capabilities and intricacies - Practical experience with full-stack development and comfort working with backend technologies - A track record of shipping impactful, high-adoption mobile applications - Strong communication and mentorship skills - Thrived in a fast-paced, collaborative environment and and enjoy working closely with cross functional partners and teammates Preferred qualifications - 0-to-1 experience building successful products in early-stage environments - Experience building applications that utilize modern ML/AI technology - 3D graphics, visual effects, and audio and video streaming on mobile - A vision for the future of human-machine interaction and a drive to make that vision a reality 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: $320,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field rele
Staff+ Application Security Engineer - M&A
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 Application Security team secures the systems that build, serve, and increasingly are Claude — and as Anthropic's footprint grows, that mandate now extends to companies and codebases we bring in from outside. This role establishes that function. You'll own security due diligence and secure integration for Anthropic's acquisitions — assessing a target's security posture pre-close, writing the security risk readout for leadership, and after close, bringing acquired systems up to Anthropic's bar. Security has been part of every deal to date, but this is the first dedicated role for it: you'll formalize the playbook, the risk model, and the tooling, and make them repeatable. This is an AppSec role first. You'll be an active member of the Application Security team — same rituals, same on-run rotation, same tooling, working alongside engineers securing Anthropic's own agentic product surfaces. The expectation is the same too: we use Claude as our primary tool, and you're expected to automate the repeatable parts of diligence and integration as you go, so each acquisition is easier than the last. When deal flow is quiet, you'll pick up core AppSec project work; when it's active, M&A is your priority. We're upfront that the center of gravity here is M&A rather than core product security. It's burstier, more assessment-heavy, and operates on confidential, time-sensitive work. If you like parachuting into an unfamiliar codebase under time pressure and turning it into a clear risk picture for leadership, this is that job. Key responsibilities - Lead pre-close security due diligence on prospective acquisitions — coordinate external penetration testing, threat-model the target's architecture, assess security controls, and deliver the security risk readout for leadership ahead of close and integration planning - Drive post-close security integration — stand up static and dynamic analysis coverage on acquired codebases, track high- and critical-severity remediation to closure, fold acquired assets into bug bounty scope, and onboard repositories to Anthropic's automated vulnerability remediation and reporting systems - Coordinate adjacent security engineering teams (supply chain, cloud, corporate security, detection & response) on their portions of each integration - Work across a wide set of stakeholders on every deal — corporate development, legal, security leadership, and the engineering teams inheriting acquired systems internally; engineering and security counterparts at the target company externally — translating between them and keeping the security workstream legible to all of them - Formalize and scale Anthropic's M&A security playbook — risk-scoring model, diligence runbook, integration checklist — and turn as much of it as possible into Claude-powered tooling rather than manual process - Share the team's operational on-run rotation (bug bounty escalations, launch consults, incident response), swapping out during periods of active deal work - Contribute to core AppSec projects between deals — secure design reviews, threat modeling for agentic systems, and the team's security automation roadmap Minimum qualifications - H
Senior Software Engineer, Database (SmithDB)
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the team SmithDB is LangChain's internal database team. We're building a storage and query layer purpose-built for AI observability and evaluation. Within six months we went from idea to a production system that offers industry leading performance and scalability for agent observability data. We're a small, fast team of systems engineers tackling genuinely hard problems: storage layout, query execution, compaction, and scaling toward trillions of agent traces. We develop in Rust, run on Kubernetes, and integrate tightly with S3/GCS/Azure Blob. There are no legacy constraints; this is a greenfield system with real production load and ambitious engineering goals. About the role We're a fast-moving team looking for a systems / database engineer to help design, optimize, and harden our system. Within 6 months, we've gone from idea to production system but there is still lots to build and optimize. You'll be working on execution, storage layout, performance profiling, and scaling to trillions of traces. This role is based in San Francisco. What you'll do - Engineer performant Rust code for ingestion and query execution - Optimize for cost and speed, heavily utilizing memory and CPU profiling - Integrate tightly with cloud object stores (S3/GCS/Azure Blob) - Deploy our distributed database services on Kubernetes (multi-tenant, high throughput, low latency) - Contribute to observability for the storage engine itself (metrics, tracing, debug tooling) What you'll bring - 5+ years in systems/database engineering with strong experience in a systems programming language (Rust, C++). Rust strongly preferred, as it is the language we use. - Knowledge of database internals is a plus: query engines, storage systems, indexing, and compaction - Proficiency in systems performance analysis: memory allocation, CPU hotspots, lock contention, async runtimes. - Familiarity with similar query execution engines is a plus - Experience with Kubernetes, distributed systems, and cloud object storage is a plus. - Strong fundamentals in networking, OS concepts, and systems debugging. Compensation Salary Range: $175,000-$240,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Senior Software Security Engineer
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team The Security Engineering team protects Anthropic's AI systems and maintains the trust of our users and society. We define the authentication architecture for our training infrastructure, design the cryptographic foundations that protect model weights and training data, and drive the developer security program that shapes how engineers build and ship software. The team works across several areas that collaborate closely: identity and secrets management, developer security and supply chain, infrastructure security, and secure frameworks. You will support one of these areas while contributing across others, with your focus shaped by your strengths and the team's priorities. Responsibilities: - Build and maintain identity and secrets management systems, including credential issuance, rotation, and workload authentication across our multi-cloud environments - Contribute to cluster security controls including RBAC policies, namespace isolation, workload identity, and pod security - Implement and maintain cloud security controls including IAM, network segmentation, VPC architecture, and encryption across our multi-cloud and on-prem environments - Design and implement secure development frameworks and libraries that make secure coding the path of least resistance for our engineering teams, including service to service authentication, serialization libraries, and tool proxies. - Harden CI/CD pipelines against supply chain attacks through isolated build environments, signed attestations, dependency verification, and automated policy enforcement - Identify and remediate security gaps through code review, threat modeling, and hands-on debugging - Contribute to continuous cloud security posture management using infrastructure-as-code scanning, misconfiguration detection, and automated remediation You may be a good fit if you have: - At least 5 years of software engineering experience implementing and maintaining security-relevant systems in production - Bachelor's degree in Computer Science or equivalent industry experience - Strong programming skills in Python or at least one systems language such as Go or Rust - Experience contributing to cloud security controls - A track record of taking ownership of problems end to end, from identifying the issue to shipping and monitoring the fix - Clear communication skills and the ability to work collaboratively across engineering teams - Low ego and high empathy, with a genuine interest in helping teammates succeed - Passion for AI safety and the role security engineering plays in building trustworthy AI systems Strong candidates may also have: - Contributions to developer security tooling including SAST, dependency scanning, or secure build infrastructure - Familiarity with Kubernetes security primitives including RBAC, namespaces, network policies, and admission controllers - Experience with cloud security posture
Staff Software Engineer, Node Infra
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 Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major cloud providers and from datacenters custom-built for Anthropic, stand up and scale the clusters behind one of the industry's largest AI compute fleets, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic's frontier AI research. Key responsibilities - Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair - Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families - Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity - Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others - Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy - Establish and evolve operational excellence practices (incident response, postmortem culture, on-call) - Support the growth of engineers around you through technical mentorship and coaching Minimum qualifications - Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure) - Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform. - Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium) - Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems - Ability to build alignment across senior stakeholders and communicate effectively at all levels Preferred qualifications - 7+ years of software engineering experience, including time as a technical lead setting direction for a team - Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency - Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines - Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons - Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads. - Demonstrated ownership of production reliability for high-throughput,
Staff+ Software Engineer, Experimentation
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 Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale. This role focuses on the configuration and experimentation systems that let teams safely roll out changes, run controlled experiments, and make data-driven decisions across our products and infrastructure — from feature flagging and dynamic configuration to A/B testing platforms that support both research and production workloads. Responsibilities - Own the technical strategy and roadmap for config and experimentation infrastructure, translating team-level goals into concrete execution plans and partnering with teams focused on deployment, testing, and more - Maintain and enhance the architecture for feature flagging, dynamic configuration, and experimentation systems, ensuring the hardest problems get solved — whether by you directly or by working through others - Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume experimentation and config workloads across all engineering teams - Own and evolve the platforms and tooling that let engineers and researchers safely ship config changes, run experiments, and measure impact - Define standards, tooling, and frameworks for experimentation and configuration management that drive developer productivity across research and production workloads You may be a good fit if you: - Have deep experience with configuration management, feature flagging, and/or experimentation platforms in a large-scale environment - Have strong proficiency in Python, Rust and/or Go - Are obsessed with developer productivity and reducing friction in how teams configure, test, and ship changes - Have experience with container orchestration and infrastructure at scale - Have excellent communication skills and enjoy supporting internal partners to improve their development experience - Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges Strong candidates may have: - Have 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure - Have 3+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams as an engineer or tech lead - Experience with config or experimentation platforms such as Statsig, GrowthBook, LaunchDarkly, Optimizely, Unleash, or similar (including building such systems in-house)</li&g
Offensive Hardware Security Engineer, Platform Sec...
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 seeking a vulnerability assessment candidate for platform security. You'll work cross functionally with teams across Anthropic and our partners to assess security features in hardware, firmware, bootloaders, operating systems, and attestation systems to identify and remove vulnerabilities from the ground up. This role requires expertise in low-level systems security and the ability to audit the most security-critical platform elements. This is not a role where you can simply file a ticket and hope that the fixes get into production and stay in production. The role requires taking ownership that everything you find is eliminated fully and correctly in production, including ensuring known vulnerabilities are never reintroduced. Key responsibilities - Audit secure boot chains from firmware through OS initialization for diverse hardware platforms (CPUs, BMCs, switches, peripherals, and embedded microcontrollers) - Audit attestation systems that provide cryptographic proof of system state from hardware root of trust through application layer - Audit measured boot implementations and runtime integrity monitoring - Integrate security controls with infrastructure teams without impacting training performance - Validate security mechanisms before production deployment - Conduct firmware vulnerability assessments and penetration testing - Build firmware vulnerability assessment pipelines for continuous security monitoring - Document security architectures and maintain threat models - Collaborate with software and hardware vendors to ensure security capabilities meet our requirements for exploit mitigation Minimum qualifications - Proven track record of conducting hands-on vulnerability auditing on complex, security-critical systems - Hands-on experience with secure boot, measured boot, and attestation technologies (TPM, Intel TXT, AMD SEV, ARM TrustZone) - Strong understanding of cryptographic protocols and hardware security modules - Experience with UEFI/BIOS or embedded firmware security, bootloader hardening, and chain of trust implementation - Proficiency in low-level programming languages (C, Assembly) and systems programming - Knowledge of firmware vulnerability assessment and threat modeling - Ability to work effectively across hardware and software boundaries - Strong communication and cross functional collaboration skills - Track record of assessing security architectures for complex, distributed systems Preferred qualifications - 8+ years of experience in systems security, with at least 5 years focused on low-level security (firmware, bootloaders, and OS kernel-level security) - Capacity to audit for logic bugs in code written in Rust or Go - Ability to find vulnerabilities via reverse engineering in software that is provided only in binary form - Experience performing f
Staff Software Engineer, Kubernetes Platform
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 run one of the industry's largest AI compute fleets, spanning multiple cloud providers and datacenters, to train, research, and serve frontier AI models. Those fleets run on Kubernetes, and the Kubernetes Platform team owns the control plane that makes them work. We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure. We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow. Key responsibilities - Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption - Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us - Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on - Build and maintain custom controllers, operators, and CRDs - Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities - Collaborate with cloud providers on required features and escalations - Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures Minimum qualifications - Significant software engineering experience building and operating production distributed systems - Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++) - Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters - Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes - A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on - Strong written and verbal communication; comfort building consensus with internal stakeholders Preferred qualifications - Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar - Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents) - Background scaling control planes or coordina
SWE Fellow - Human Frontier Collective (US)
PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do - Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex, domain-specific problems and datasets to rigorously evaluate AI models, and provide expert insights that enhance their accuracy, reasoning, and overall performance. - HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. - Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply - Professional and Academic Background: 5+ years of software engineering or related technical experience, or equivalent domain expertise through academic work (e.g. PhD, postdoctoral research, or faculty experience in Computer Science or related field). - Skills: Demonstrated coding proficiency and analytical abilities, with deep expertise in one or more of the following programming languages: Python, Java, Rust, Swift, JavaScript, or C++. - Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration. Why Join the HFC? - Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research—while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology. - Join a Top-Tier Network: Collaborate with a global network of academics and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions. - Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments. - Competitive Pay: Project pay rates vary across platforms and ar
SWE Fellow - Human Frontier Collective (UK)
PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the country they reside in. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do - Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex, domain-specific problems and datasets to rigorously evaluate AI models, and provide expert insights that enhance their accuracy, reasoning, and overall performance. - HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. - Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply - Professional and Academic Background: 5+ years of software engineering or related technical experience, or equivalent domain expertise through academic work (e.g. PhD, postdoctoral research, or faculty experience in Computer Science or related field). - Skills: Demonstrated coding proficiency and analytical abilities, with deep expertise in one or more of the following programming languages: Python, Java, Rust, Swift, JavaScript, or C++. - Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration. Why Join the HFC? - Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research—while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology. - Join a Top-Tier Network: Collaborate with a global network of academics and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions. - Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments. - Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location. Application Process </h3&g
Sr. Customer Engineer, Central & Eastern Europe -...
About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations Amsterdam, Netherlands and London, United Kingdom About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. What you will do as a Customer Engineer The Sr. Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey. You will bridge the gap between technical strategy and business value—guiding enterprise clients from initial pre-sales technical validation through onboarding, deployment architecture, and full lifecycle expansion. Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off you
Staff Product Manager, Physical AI Data & Robotics
Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions. The next frontier for AI is the physical world. We're looking for an AI Product Manager to own the Robotics vertical within our Physical AI team. In this role, you'll own both the development of the data and training environments (the teleoperated demonstrations, real-world collections, simulated tasks, and annotation products that labs use to train and evaluate robot policies) and the "data as a product" strategy that powers them. You'll understand where physical AI is headed, decide what robot tasks and embodiments are worth collecting, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside robotics or physical AI research, and is able to pair that domain understanding with a sense for where current robot policies succeed and fail in real-world workflows. You'll translate that expertise into datasets, environments, and evaluation frameworks that teach robots to do real physical work, and you'll be the domain expert Scale's most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You'll Do - Own the Robotics AI roadmap & data strategy: Set product direction for the robotics training stack and the data strategy behind it — what data we collect, on which hardware and embodiments, and what we source internally vs. through our marketplace. Establish a vision for where physical AI is heading, driving execution across engineering, operations, and go-to-market teams. - Build partnerships with research teams at frontier labs: Work directly with researchers at leading physical AI labs to understand where their robot policies fall short and shape new product lines and competitive strategy for the vertical. Connect with robotics startups and industry leaders to launch joint benchmarks and build Scale's brand in physical AI. - Design and scale robotics data products and environments: Scope and deliver high-quality collection pipelines, annotation tooling, simulated tasks, and evaluation frameworks — spanning robot-based collection (humanoids and robotic arms performing real-world tasks) and robot-less collection (wearable cameras capturing human demonstrations). Partner with ML and Operations to translate research needs into training products that hit quality, throughput, and cost targets. - Collaborate cross-functionally — influence business priorities and dive into the weeds of research, operations, and customer interactions to deliver mission-critical outcomes. Travel ~10–15% to meet customers, attend conferences, and visit our global data operations. Ideally, You'd Have - 8 years of PM experience and 3 years of experience in robotics or physical A I in one or more of: robot learning or manipulation research, teleoperation and data collection systems, robotics software or hardware engineering, or a robotics product role, with real depth in how the work gets done. - Physical AI Fluency: Immersed in current physical AI research — robot p
ML Research Intern
ABOUT US: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C https://modal.com/blog/modal-series-c at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. Preferred Qualifications: 1. Currently pursuing a PhD in computer science, machine learning, or a related field. 2. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. 3. Experience developing and evaluating large-scale models or machine learning systems. 4. Familiarity with distributed training, large-scale inference, or multi-GPU environments. 5. Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR. 6. Strong programming and engineering skills, with the ability to translate research ideas into working implementations. 7. A collaborative, mission-driven mindset and the ability to work effectively across research and engineering teams.
Member of Technical Staff (Software Engineer, Stor...
About the Role The Storage Platform team owns the infrastructure that powers how Perplexity persists, retrieves, and manages data across all systems, ensuring high availability, performance, and cost-efficiency for every product and AI workload. This foundational, high-impact group is responsible for the full spectrum of storage technologies – relational databases, vector databases, custom storage implementations, and the tooling to provision, monitor, and optimize them at scale. By building robust abstractions and operational excellence around storage, the team enables engineers across Perplexity to focus on product innovation while trusting that data is fast, reliable, and always accessible. KEY RESPONSIBILITIES - Design, operate, and continuously improve the storage platform that underpins all Perplexity products and AI workloads, including relational, NoSQL, and vector databases. - Own reliability, performance, and availability SLOs for stateful systems, driving root cause analysis and long‑term fixes for storage‑related incidents. - Define and evolve opinionated storage abstractions, APIs, and tooling that make it simple and safe for product teams to consume storage at scale. - Partner with AI, infra, and product teams to design data models and access patterns that meet low‑latency, high‑throughput, and cost‑efficiency requirements. - Lead capacity planning, benchmarking, and lifecycle management for storage clusters, including scaling, migrations, and deprecations. QUALIFICATIONS - 5+ years of experience building and operating large‑scale backend or infrastructure systems in production. - Deep hands‑on experience with at least one major database technology (for example, Postgres, MySQL, DynamoDB, Cassandra) and familiarity with modern cloud storage services. - Strong fundamentals in distributed systems, data modeling, and performance optimization for high‑throughput, low‑latency workloads. - Proven track record of owning services end‑to‑end, including design, implementation, deployment, and on‑call. - Proficiency in at least one programming language used for backend systems (such as Go, Rust, or Python). - Effective communication and collaboration skills, with the ability to partner closely with product, infra, and AI teams. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.
Software Engineer, ML Networking
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. Role Summary A systems-level engineer specializing in network infrastructure and network optimization, with expertise in building and maintaining software that interacts with networks. You will be responsible for writing and maintaining software that interfaces between our accelerators and our high-speed networks. This role requires deep technical knowledge of network protocols, kernel-space and/or user-space networks, interfacing with hardware, and the ability to debug and optimize distributed software at the network level. You may be a good fit if you have: Networking Systems Engineering: - Expert-level proficiency with network protocols and networking concepts - Deep kernel networking: TCP/IP stack internals, XDP, eBPF, io_uring, and epoll - User-space networking: DPDK, RDMA, kernel bypass techniques - Understanding of how to build higher-level abstractions like collectives and RPC - Skilled at diagnosing and resolving networking issues in distributed systems, especially at OSI model layers 2-4 Low-Level Systems and OS Programming: - Strong programming skills in a systems programming language, including memory management, lock-free data structures, and NUMA-aware programming - Software, driver, and OS performance optimization tools and techniques - Comfort with or desire to learn Rust Strong candidates may have: - Understanding of ML accelerators and accelerator drivers - Demonstrated ability to design new network protocols - Experience with PCIe and drivers for PCIe devices - Expertise in algorithms used in networking, including compression and graph algorithms - Experience programming on SmartNICs - 5+ years of experience in systems programming or network programming - Often comes from backgrounds in: HPC, telecommunications, host networking software, OS/kernel engineering, or embedded systems - Strong debugging mindset with patience for complex, multi-layered issues Representative Projects: - Build a system for accelerator-initiated tensor movement over the network - Benchmark software for a new networking environment - Implement a new collective algorithm to improve latency - Optimize congestion control algorithms for large-scale synchronous workloads - Debug kernel-level network latency spikes 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: <div class="pay-range"&g
Member of Technical Staff (Backend/Infrastructure...
Perplexity is looking for an Infrastructure Engineer to own and improve the backend systems behind our latency-sensitive search stack. You’ll work across high-QPS Rust and Go services, distributed retrieval systems, cloud infrastructure, observability, and deployment tooling. This role combines infrastructure expertise with software engineering. You’ll take systems from design through production operation and use AI-native tools where they meaningfully improve engineering and operational workflows Responsibilities - Build and operate scalable, low-latency infrastructure for search serving and retrieval. - Design and improve distributed backend systems that handle high request volumes. - Debug and optimize Linux systems, containers, networking, and production services. - Improve reliability through observability, capacity planning, performance profiling, and incident response. - Design, deploy, and operate cloud-native systems, primarily on AWS and Kubernetes. - Build internal tools and automation for development, testing, debugging, and infrastructure operations. - Improve CI/CD pipelines, release processes, and production rollout safety. - Contribute directly to product codebases across Rust, Go, and other systems languages. - Own systems end to end, from architecture and implementation to deployment and production operation. Requirements - Strong experience with cloud infrastructure, distributed systems, and automation. - Deep understanding of Linux internals, performance analysis, and production debugging. - Experience building or operating latency-sensitive, high-throughput backend systems. - Experience with containers, orchestration, observability, and infrastructure as code. - Experience building or maintaining CI/CD systems and release tooling. - Fluency in at least one systems language, such as Rust, Go, C++, or Java. - Comfort working across infrastructure and application-level code. - Strong ownership and the ability to operate effectively in a fast-moving environment. Nice To Have - Experience with search, retrieval, ranking, or other large-scale data-serving systems. - Experience operating Rust services in production. - Experience with AWS, Kubernetes, and modern observability systems. - Experience with profiling, capacity planning, and performance optimization. - Experience building AI-assisted developer or operational tooling.
Full Stack Software Engineer, Education
About the team OpenAI’s Education team is building products and experiences that help learners, educators, and institutions benefit from AI in ways that are rigorous, useful, and grounded in real learning outcomes. The work spans both consumer and B2B education, with close collaboration across engineering, learning science, design, data, and research. This team sits in a highly strategic investment area for OpenAI, with strong opportunities to shape how product ideas flow across consumer and institution-facing experiences. Some of our recent work: - New Education Plugins for ChatGPT Work and Codex - New tools for understanding AI and learning outcomes - Education for countries - Advancements in higher education - Early product work - Introducing Study Mode About the role We’re looking for a product-minded Full Stack Engineer to help build OpenAI’s education products from the ground up. You’ll own end-to-end development across the stack, from early concepting and prototyping through production launch and iteration. This is an opportunity to work on a highly strategic, early-stage product area where engineering judgment, product sense, and customer empathy all matter. You’ll partner closely with leaders across the education org, including learning scientists, researchers, designers, and cross-functional partners, to turn emerging ideas into durable product experiences for schools, universities, and other education stakeholders. In this role, you will: - Build and ship product experiences across the full stack for OpenAI’s education offerings - Own projects end-to-end, from ideation and technical design through implementation, launch, and iteration - Work closely with learning scientists and researchers to translate learning goals and evidence into product decisions - Collaborate with design, data, and cross-functional partners to build thoughtful, high-quality user experiences - Help define the engineering foundation for a growing education pod, including patterns, systems, and technical direction - Contribute to products that may inform both consumer and B2B education experiences over time Your background might look something like: - 5+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies - Former founder, or early engineer at a startup who has built a product from scratch is a plus - Proficiency with TypeScript, React, and other web technologies - Proficiency in one or more backend languages (e.g., Python, Go, Rust, Typescript or similar) and distributed systems concepts - Some experience with relational databases like Postgres/MySQL - Care deeply about reliability, safety, and performance in production environments. - Interest in AI/ML (direct experience not required) - Proven ability to thrive in fast-growing, product-driven companies by effectively navigating loosely defined tasks and managing competing priorities or deadlines. - Have experience building interactive educational tools or learning products, or are excited to apply your skills in this space - Have a strong interest in improving access to education and expanding opportunities for learners worldwide About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Pre-training Distributed Systems Tech Lead / Manag...
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 is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We're looking for an experienced tech lead to join our Evals Infrastructure team, building the systems that let us measure what our models can actually do. Evaluation is how we know whether a model is safe to ship — you'd own the infrastructure that makes those measurements fast, reliable, and trustworthy at scale. In this role you'll work at the intersection of inference, research and infrastructure engineering: managing the large scale distributed systems that orchestrate evals for our frontier models, building and scaling the harnesses researchers use to design and run evals, making results reproducible and interpretable, and ensuring eval signal is available where decisions get made. Your work directly shapes what we build and what we don't. Responsibilities - Lead the team building the distributed systems that schedule, orchestrate, and execute evals for our frontier model training - Own eval throughput and cost: compute allocation across suites, queueing against constrained accelerator pools, caching and reuse of eval work - Build and scale the harnesses researchers use to define, run, and iterate on evals - Make eval results trustworthy — determinism, reproducibility, and honest uncertainty quantification on reported metrics - Ensure eval signal reaches the dashboards and reviews where launch decisions actually get made - Contribute directly as an engineer while managing and growing the team, prioritizing its work, and coaching your reports You may be a good fit if you - Have led technical projects end-to-end on large-scale distributed systems, and have 1+ years managing engineers (or tech-lead-with-reports experience) - Are strong in Python and Rust - Have built high-throughput, fault-tolerant systems on cloud or on-prem accelerator fleets - Care about measurement quality, not just pipeline uptime — you'd notice if a metric moved for the wrong reason - Communicate well with researchers and can translate research needs into infrastructure - Are deeply interested in the transformative effects of advanced AI and committed to safe development Strong candidates may have - Worked on LLM inference or training infrastructure - Experience with eval or benchmarking systems, especially agentic evals requiring sandboxed execution - Working statistical literacy — variance, confidence intervals, sample-size sufficiency for noisy metrics - Experience with observability and regression detection over time-series metrics Sample Projects - Rebuilding the eval orchestration layer to cut wall-clock time on the pre-train eval suite - Designing compute allocation and scheduling so eval suites fit inside a fixed fraction of a prod
SWE Fellow - Human Frontier Collective (Canada)
PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in Canada; visa sponsorship is not available for this role. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do - Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex, domain-specific problems and datasets to rigorously evaluate AI models, and provide expert insights that enhance their accuracy, reasoning, and overall performance. - Join the HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. - Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who Should Apply - Professional and Academic Background: 5+ years of software engineering or related technical experience, or equivalent domain expertise through academic work (e.g. PhD, postdoctoral research, or faculty experience in Computer Science or related field). - Skills: Demonstrated coding proficiency and analytical abilities, with deep expertise in one or more of the following programming languages: Python, Java, Rust, Swift, JavaScript, or C++. - Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration. Why Join the HFC? - Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research—while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology. - Join a Top-Tier Network: Collaborate with a global network of academics and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions. - Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments. - Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location. Application Process - Apply: We review applications on a rolling basis. - Interview: Candidates will meet
Staff+ Software Engineer, Infrastructure (Distribu...
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 Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models, including data pipelines, some of the largest Kubernetes clusters in the world, along with the databases, observability, and developer tooling that every other team at Anthropic depends on. As a Staff+ Software Engineer on our Infrastructure team, you'll independently scope and lead complex, multi-month infrastructure projects, make the architectural decisions other engineers build on, and work closely with research and product teams to understand their needs and build systems that keep pace as those needs evolve. - Team placement happens after the interview process, based on your interests and experience alongside organizational needs. This lets us match you with the team where you'll have the most impact. Key responsibilities - Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system - Make architectural decisions that shape the foundation of infrastructure other engineers and teams build on - Drive alignment on technical direction across multiple teams, working through ambiguous problem spaces - Partner with research and product teams to understand their infrastructure and compute needs, and translate them into technical designs - Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow - Set technical strategy and standards for your team's infrastructure - Build and improve operational processes, such as incident response, postmortems, and on-call rotations, that help the team learn from every incident - Mentor other engineers and help raise the technical bar for the team Minimum qualifications - Experience designing, building, and operating large-scale distributed systems or infrastructure in production - A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects - Experience making architectural decisions that other engineers and teams build on top of - Strong software engineering fundamentals and proficiency in at least one programming language (for example, Python, Rust, Go, or Java) - Experience with modern cloud infrastructure, including Kubernetes and infrastructure-as-code, on AWS and/or GCP - Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders Preferred qualifications - 10+ years of software engineering experience, not including internships - Experience with machine learning infrastructure, such as GPUs, TPUs, or Trainium, and associated networking infrastructure like NCCL - Low-level systems experience, such as Linux kernel tuning or eBPF - Background in security or privacy engineering best practices - Prior experience as a
Product Manager, Research (Code)
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 As a Product Manager for the Research team at Anthropic, you will own the ideation and deployment of new models and products as we advance frontier, safe AI technology. You will work closely with our research teams to help productize credible applied research and identify high-potential use cases grounded in customer needs. We are looking for someone passionate about developing safe and beneficial artificial intelligence technologies. You thrive in ambiguous environments and can uncover latent, non-obvious use cases for nascent technologies, bringing these insights back to research. Your curiosity about user needs enables you to connect advanced technology to products that deliver real-world value. We seek experienced founders and product managers who can bridge research and ambitious product experimentation, with the ability to create and grow entirely new product categories enabled by AI. Responsibilities - Lead vision, strategy, roadmap, and execution of frontier technologies that leverage the latest AI capabilities to solve real-world problems - Partner with research to define, improve, and ship model capabilities within a research area - Identify nascent research that could become transformative products - Synthesize user insights into actionable requirements and evaluations - Understand the AI landscape and ecosystem, ensuring we have an objective view of market capabilities and our position - Work with and influence a diverse set of stakeholders, including research, product engineering, and platform engineering teams Minimum Qualifications - Have a deep passion and curiosity for AI and LLMs. Use AI regularly. - Are a first-principles thinker with the ability to navigate and execute amidst ambiguity, flexing into different domains based on the business problem at hand and finding simple, easy-to-understand solutions - Possess a deep technical background with a strong grasp of AI/ML concepts and are willing to go deep on technical solutions; have a data-driven mindset with working proficiency in Python and SQL - Have strong user empathy and the ability to synthesize vague or contradictory feedback into actionable priorities - Have a track record of launching ambitious products that have achieved distribution or commercial success - Have intellectual curiosity without ego—comfortable asking questions and learning independently - Think creatively about the risks and benefits of new technologies, moving beyond past checklists and playbooks - Have a creative, hacker spirit and love solving puzzles Preferred Qualifications - Have 5+ years in product management, with experience launching new products and scaling existi
Staff+ Infrastructure Engineer, Cluster Infrastruc...
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 Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world. Key responsibilities - Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning - Partner across teams to ensure new compute capacity is ingested on time - Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity - Collaborate with security owners to ensure clusters are provisioned secure-by-default - Define and drive strategy on cluster scalability, homogeneity and fault tolerance - Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy - Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health - Support the growth of engineers around you through technical mentorship and coaching Minimum qualifications - Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure) - Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform. - Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems - Ability to build alignment across senior stakeholders and communicate effectively at all levels Preferred qualifications - 10+ years of software engineering experience, including time as a technical lead setting direction for a team - Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes) - Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like) - Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield) - Experience with cluster and host networking: CNI (Cilium), eBPF,
Member of Technical Staff (Software Engineer, Desk...
Perplexity AI is looking for experienced Generalist Software Engineers to join our Perplexity and Comet application teams. Our team is reshaping knowledge work through our high-impact desktop and Comet apps. The ideal candidate should have strong programming skills and multiple years of experience shipping high-quality, production software. Our stack spans several different skillsets, including Rust, Kotlin, Swift, Typescript, Chromium and Perplexity’s core AI stack. We have found that our strongest engineers are capable of working across multiple codebases and ramping up quickly, and we expect the same high bar for candidates. Responsibilities - Work closely with product teams to implement novel mobile experiences. - Work closely with design teams to design fast and intuitive UI. - Utilize Perplexity Computer and other Agentic coding tools to accelerate development. - Collaborate with data science and machine learning teams to instrument, analyze, and improve the end-to-end experience. - Work with infrastructure and QA teams on deployment processes, including testing, release, and monitoring. Requirements - 4+ years industry experience - Experience in shipping high-quality native applications - Architecture experience in writing code understandable by both agents and humans - Deep understanding of app performance - Ability to own projects and surfaces, and to push them forward proactively
Staff Software Engineer, Infrastructure (Distribut...
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 Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models. That includes data pipelines, some of the largest Kubernetes clusters in the world, and the databases, observability, and developer tooling that every other team at Anthropic depends on. As a Staff Software Engineer on the Infrastructure team, you'll scope and lead complex, multi-month infrastructure projects, make the architectural decisions other engineers build on, and work with research and product teams to build systems that keep pace as their needs change. Team placement happens after the interview process, based on your interests and experience alongside organizational needs. This helps us match you with the team where you'll have the most impact. Key responsibilities - Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system - Make architectural decisions that shape the foundation other engineers and teams build on - Drive alignment on technical direction across teams, working through ambiguous problem spaces - Partner with research and product teams to understand their infrastructure and compute needs, and turn them into technical designs - Own the reliability, scalability, and security of the systems you build as usage and complexity grow - Set technical strategy and standards for your team's infrastructure - Build and improve operational processes such as incident response, postmortems, and on-call rotations, so the team learns from every incident - Mentor other engineers and help raise the technical bar for the team <h2 class="mt-3 -mb-1 text-[1.125rem] font-bold" data
Internship - Search Machine Learning Engineer
Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information. Internship program: 12 - 24 weeks, full-time, part-time, in-person in the Belgrade office. Responsibilities: - Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers. - Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models. - Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks. - Support deployment and monitoring of search and ranking models in a scalable and performant way. - Help build and iterate on RAG pipelines for grounding and answer generation. - Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML. Qualifications: - Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems. - Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects. - Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required. - Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required. - Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment - Experience with Rust will be a plus What we're looking for: - You’ve built something you’re proud of: Not just a class assignment - we want to see a project you genuinely cared about and took the initiative to build and finish. - You’re currently enrolled at a Serbian university: Bachelor’s, Master’s, or PhD program or you’re self-taught with a strong passion for software engineering and technology. - You’re curious, persistent, and self-driven: you take ownership, work through challenges, and follow through on what you start. - You’re eager to learn and improve: you’re willing to put in the work, develop your skills, and get better every week. - You’re comfortable working in English: in a collaborative, professional environment. - You thrive in a high-performance environment: you’re comfortable with high standards, direct feedback, and a fast pace. - You’re willing to challenge and be challenged: You’re comfortable asking questions, sharing your perspective, and pushing back constructively when it matters.
Staff+ Software Engineer, Claude App Infrastructur...
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 Claude App Infrastructure owns the reliability, experience, and agentic capabilities of claude.ai. We're the platform team for Anthropic's flagship consumer product, responsible for the serving architecture that keeps Claude available at scale, the conversation experience, and the infrastructure that lets every product team at Anthropic ship into claude.ai safely and fast. When the product grows at hyper scale, we're the team that makes sure it feels the same or better. Beyond the foundation, we're building the agentic layer that turns claude.ai from a chat surface into an execution surface: task execution, personalization, browser use, and server-side tools. This is where the next generation of the product gets built: the primitives that let Claude act in the world, not just respond. We believe reliability and velocity are the same problem, and our job is to build the systems that make both inevitable. Key responsibilities - Design and build sandboxed compute environments where Claude can safely execute code, access tools, and interact with external services - Build state management systems for long-running agent tasks, handling checkpoints, recovery, and resumption across failures - Develop authentication and authorization frameworks for delegated access, so Claude can act on behalf of users securely - Create observability and debugging tools for agent execution, so we understand what Claude did, why, and how to make it better - Partner closely with product and research teams to define what's possible and ship it Minimum qualifications - Experience building distributed systems, infrastructure, or platform services at scale <li class="font-claude-response-body whitespace-normal break-words pl-2" data-sourcepos="22:1-2
Staff + Sr. Software Engineer, Cloud Inference Lau...
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 The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations. Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact. This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource. Key responsibilities - Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform - Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production - Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds - Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production - Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability - Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads Minimum qualifications - Have a strong interest in LLM serving; prior inference or ML experience is not required - Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users - Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability - Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration - Thrive in cross-functional collaborati
Staff+ Software Engineer, Infrastructure, Interpre...
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: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic works to understand what's actually happening inside trained models - and applies our best techniques to keep frontier AI safe as it rapidly improves. Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs. More resources to learn about our work: - Our Research blog - covering advances including Monosemantic Features and Circuits - An Intro to Interpretability from our research lead, Chris Olah - The Urgency of Interpretability from CEO Dario Amodei - Engineering Challenges Scaling Interpretability - directly relevant to this role - 60 Minutes segment - see a demo of tooling our team built - New Yorker article - what it's like to work on one of AI's hardest open problems This role is an early hire on a new infrastructure effort within Interpretability: you'll help define its charter, not just execute it. Interpretability research requires deep access to frontier models while retaining a high degree of research flexibility. Your job is to build the paved path that makes that access secure by default, private by design, and low-friction for every researcher. The work spans four areas: - Security : design the secure-by-default environments and access patterns that enable deep model access for an organization whose research requires it - done well, the same design improves both our security posture and research productivity. - Privacy : build data-access patterns that ensure policy adherence as our research moves from theory into practical application - Data & Compute Management : manage research data at petabyte scale and make efficient use of large accelerator fleets - storage lifecycle, capacity planning, and scheduling. - Developer experience : agentic engineering
Platform Security Engineer, OpenBMC
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 is standing up a founding team to own the server management firmware running across its server fleet. You would be one of the first engineers on it. That means production firmware and manageability features (board bring-up through production) on one side, and hardening that firmware against sophisticated adversaries on the other. Security is a first-class constraint in everything you ship: you'll write firmware to a high security bar and partner closely with our firmware security and hardware engineers on secure boot, signing, and attestation. Key responsibilities Production and manageability: - Design, build, and ship OpenBMC firmware and manageability features for x86 and Arm (including GPU) platforms, from bring-up through production, using Yocto/OpenEmbedded - Build the management stack on DMTF/OCP standards (MCTP, PLDM, SPDM, Redfish, RDE) and IPMI/KCS: sensors, telemetry, inventory, logging, RAS - Implement BMC-to-BIOS/host communications, eSPI/LPC, thermal/fan/power management (PMBus) - Work the hardware/firmware boundary: I2C/I3C, SPI, PCIe, SMBus, device trees, U-Boot, Linux Security and hardening: - Own the BMC security posture: secure and measured boot, root of trust, attestation (SPDM), authenticated update (PLDM FW Update), rollback protection, attack-surface reduction - Lead threat modeling and secure design reviews; run coordinated vulnerability disclosure with vendors and the upstream community - Build verification tooling: static analysis, fuzzing, firmware extraction, CI gating Minimum qualifications - Strong technical cross-functional leadership skills, direction setting - Hands-on OpenBMC/BMC firmware experience on x86 and/or Arm, from bring-up through production with hands-on D-Bus/sdbusplus - Strong C/C++ and Python, deep Linux user-space/kernel fundamentals, and Yocto/OpenEmbedded proficiency - A security mindset applied to firmware, not bolted on afterward - Upstream contributions to OpenBMC, U-Boot, DMTF, or OCP - Working knowledge of out-of-band and in-band management, the relevant DMTF specs, and the device interfaces they run over - Strong debugging and a track record of shipping reliable, well-tested code. - Clear communication across internal teams and external vendors - Ability to work effectively across hardware and software boundaries - Knowledge of NIST firmware security guidelines and hardware security frameworks, specifically SP 800-193 and 800-147/155 Preferred qualifications - 8+ years of experience in systems security, with at least 5 years focused on firmware and hardware security (firmware, bootloaders, and OS-level security) - Hardware roots of trust and attestation: Caliptra, OCP S.A.F.E., TPM/HRoT, SPDM - Memory-safe systems code in Rust or Zig - Firmware vulnerability research, re
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