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Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Technical Program Manager for Product, you'll drive the programs that bring Anthropic’s AI capabilities to the world. You’ll work closely with research teams to understand new model capabilities, then orchestrate across engineering, product, infrastructure, and go-to-market teams to ensure we launch reliably and at pace. This role is essential in orchestrating the cross-functional effort required to launch successfully as Anthropic continues to scale. This role offers unique challenges in coordinating high-stakes technical programs while maintaining the quality and reliability our customers expect. This position requires deep technical fluency, the ability to earn trust with researchers and engineers, and a talent for driving alignment across teams with different priorities and working styles. Responsibilities Lead end-to-end program management for model and product launches, coordinating between research, engineering, product, infrastructure, and partnership teams Drive cross-functional alignment and decision-making across workstreams, ensuring teams are unblocked and launches stay on track Partner closely with Research PMs and engineering leads to sequence work, manage dependencies, and navigate technical tradeoffs Track and communicate program status, risks, and dependencies to leadership and stakeholders Build strong relationships with technical stakeholders, earning trust through deep engagement with the details Coordinate with research teams to understand upcoming model capabilities and prepare launch plans accordingly Navigate tradeoffs between speed, quality, and scope, helping teams make informed decisions under pressure Develop and improve launch processes, playbooks, and operational frameworks that scale with our growing complexity Create and maintain documentation of launch processes, decision logs, and cross-functional dependencies You may be a good fit if you Have several years of experience in technical program management, with a track record of successfully delivering complex, cross-functional programs Possess deep technical knowledge that allows you to engage meaningfully with ML researchers and engineers Have experience managing programs with significant external dependencies and multiple stakeholder groups Excel at translating between technical teams and stakeholders, making complex tradeoffs understandable Can thrive in ambiguous situations, bringing structure to complex technical challenges Have strong organizational skills and can manage multiple parallel workstreams effectively Are comfortable operating at a fast pace where priorities shift and new challenges emerge quickly Have excellent written and verbal communication skills, with the ability to influence without authority Build trust quickly and maintain strong relationships even under pressure Are passionate about Anthropic's mission and interested in the challenges of bringing frontier AI capabilities to users safely 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: $365,000 — $435,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role 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, NetworkPolicy, multi-NIC, sFlow, service mesh (Istio/Envoy/Linkerd, mTLS) Experience with cluster security: pod security standards and admission control, RBAC and least-privilege IAM, node and container hardening, supply-chain/image provenance Deep experience with infrastructure-as-code (Terraform, Atlantis), workflow orchestration (Temporal, Argo Workflows) Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software 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: $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.

Location: Dublin, IE; London, UK; New York City, NY; Remote-Friendly, United States 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 an Incident Response Manager to serve as the operational backbone of how Anthropic handles incidents. When things go wrong, you are the person who makes sure the right people are in the room, the right information is flowing, and nothing falls through the cracks. The right person for this role brings structure and rigor to high-volume, high-stakes situations without waiting for a playbook to be handed to them. You will work across engineering, product, security, legal, go-to-market, and leadership to ensure Anthropic responds to incidents with speed, clarity, and accountability. This is not a role where you follow existing runbooks; it is a role where you write them, and where you operate effectively even when the runbook does not yet exist. Responsibilities Build the incident response management function, establishing the processes, tooling, and operational standards that define how we handle incidents at scale Serve as an on-call incident commander, driving coordinated response across technical and non-technical stakeholders during incidents of varying severity, including managing multiple active incidents simultaneously Engage the right people at the right time, with a strong sense of urgency, bringing order and direction to fast-moving, ambiguous situations Own incident communications end-to-end, from real-time internal coordination to external channels like status pages, direct customer outreach, and stakeholder updates, ensuring they reflect Anthropic's commitments to safety, transparency, and accuracy Participate in blameless incident reviews, contributing operational context and helping drive follow-through on critical remediations so the same class of incident does not recur Partner with engineering teams to develop and maintain incident response policies, procedures, and escalation frameworks that scale with Anthropic's growth Partner with engineering, product, security, legal, and go-to-market teams to continuously improve how the organization detects, responds to, and learns from incidents You May Be a Good Fit If You Have 5+ years of experience in incident management, with direct experience managing technical product or infrastructure incidents (not exclusively security or trust and safety) Have built or significantly shaped an incident response program, ideally at a high-growth startup or in an environment where you had to create structure rather than inherit it Demonstrate a strong sense of ownership and urgency, with the ability to operate independently and make sound decisions under pressure without waiting for direction Are comfortable working in unprecedented situations where processes are still being defined and guidance may be incomplete or conflicting, leaving things better than you found them Have a track record of effective cross-functional collaboration, particularly with engineering, security, legal, communications, go-to-market, and executive leadership Bring a blameless, learning-oriented mindset to incident reviews, focused on systemic improvement rather than individual fault Have experience with cloud infrastructure incidents and enough technical depth across the stack to engage meaningfully with engineering teams during response, including comfort navigating distributed systems, monitoring tools, and logs Are analytically minded, with experience using data (incident metrics, queries, trend analysis) to inform decisions during response and to drive operational improvements over time Communicate clearly and calmly under pressure, both in real-time coordination and in post-incident written communications Thrive in high-volume, fast-paced environments and are energized by bringing operational discipline to complex, evolving situations 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: $290,000 — $365,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's Human Data Platform team builds systems designed to collect data that improves our models. This includes the infrastructure to simulate real-world environments and tasks, novel interfaces for data vendors to use, and the pipelines that enable researchers to gather high-quality data at scale. As Claude's real-world usage evolves, so do our data needs — and our tooling has to keep pace. You'll work alongside an engineering team that's quickly prototyping and shipping, help make smart bets about where to focus, and ensure we're investing in tooling that scales. You'll work across research teams, data ops, and external vendors, translating what you learn into clear direction on what to build next. Responsibilities Own the product direction for our human data tooling, with clear prioritization across labeling interfaces, infrastructure investments, data quality, and operational visibility Partner with engineering to scope and ship quickly, staying close to the work in a fast-moving prototyping environment Develop a deep understanding of research and training approaches to identify where tooling investments will have the highest leverage Identify patterns across one-off requests and push toward reusable infrastructure that compounds over time Sit in on crowd worker and vendor sessions to systematically understand pain points Define and track outcome-based KPIs: time-to-launch for new data collection projects, end-to-end data quality scores, and measurable impact on model evaluation scores Minimum Qualifications You May Be a Good Fit If You Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well Are drawn to ambiguous, high-stakes environments where you’ll play a big role in defining the product strategy Shipped products where they had to deeply understand technical constraints, not just translate requirements Experience working directly with research teams, ideally in AI/ML contexts Are equally comfortable talking to crowdworkers about their workflow and to research teams about data quality methodology Are a quick study—this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level) to be effective Have an interest in how humans interact with AI systems and how to design experiences that elicit high-quality data Preferred Qualifications Strong Candidates May Also Have Experience building data collection tools, annotation platforms, or human-in-the-loop pipelines Experience working with researchers who are internal users/customers Good instincts and an eye for intuitive user experiences, particularly those involving complex UI interactions or annotation workflows Strong project management skills: prioritization, communicating across team/org boundaries The ideal candidate has the following virtues/values: Have 5+ years in product management, with experience launching new products and scaling existing products. Intellectual curiosity without ego: Comfortable not knowing things and asking questions to learn Autonomous learning: Able to independently figure out how systems work and develop expertise quickly Researcher EQ: Deep understanding of how researchers think and what motivates them Product creativity: Ability to see novel product opportunities emerging from research capabilities Founder mentality: Track record of doing whatever it takes to ship highly technical products 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: $305,000 — $385,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's research organization works across the full model development lifecycle, from pre-training and post-training to alignment, interpretability, and safety, each operating at the frontier of AI development. As a Technical Program Manager for Research, you'll define and build the programs that research teams need most. You'll move across research areas like compute, evals, RL environments, and emerging research initiatives, going deep enough in each to understand how researchers work and what they need. You'll identify where the biggest opportunities for impact lie, find the highest-leverage gaps, and build the programs, processes, and tooling that allow researchers to focus on research. This is a 0-to-1 role: you'll explore new domains as priorities shift, determine what each one needs, and create lasting impact where none existed before. Note: This role may require responding to incidents on short-notice, including on weekends. Responsibilities Embed deeply within a research domain to understand the technical landscape, build trust with researchers and technical leaders, and identify the highest-leverage problems to solve, knowing the surface area will shift over time as research priorities evolve Move fluidly across research areas like compute, evals, RL environments, and emerging research initiatives, picking up new domains quickly and getting to depth fast Drive end-to-end execution of complex, ambiguous research initiatives spanning multiple teams, often without established playbooks or precedent Establish processes and frameworks that bring structure to unstructured research environments without slowing researchers down Lead efforts like large-scale compute resource planning, including allocation, efficiency, and prioritization across research and production workstreams Drive eval readiness for model launches by standardizing results, shaping eval plans early, improving tooling, and ensuring honest, transparent reporting across research, product, and marketing Own execution and operational health of RL environments across major training runs, coordinating cross-team trade-offs and feeding insights back into roadmap planning Equip research leadership to make decisions quickly by going deep on technical tradeoffs and presenting clear, actionable recommendations Act as the connective tissue between research, engineering, and product teams to reduce chaos and accelerate execution You May Be a Good Fit If You Have a background in ML research or engineering with several years of experience building technical programs from scratch, ideally with hands-on exposure to training, evaluation, or large-scale distributed systems Are a fast learner who can ramp on unfamiliar technical domains quickly and contribute meaningfully to discussions with researchers Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in fast-moving research environments Have a track record of operational ownership of complex technical systems, including monitoring, incident response, and performance optimization Can reason about technical tradeoffs at depth across model architecture, training infrastructure, evals, or compute efficiency, and translate them into clear decisions for leadership Have excellent stakeholder management skill and the ability to influence senior technical staff through competence and consistent delivery Are comfortable with high-stakes environments where decisions impact compute spend, model training timelines, and launch outcomes Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems Are excited to redefine what technical program management looks like at the frontier of AI research 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: $365,000 — $435,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Toulouse, France; United States; United Kingdom The company provides full relocation support, including immigration assistance, and offers a relocation bonus upon arrival in Montreal. Selected candidates may work remotely during the initial months while their immigration process is being completed; however, the long-term expectation is for the individual to transition to onsite work in Montreal once relocation has been finalized. Tasks summary: Architecture Concept & Requirements • Gather functional, performance, environmental and security requirements from mission stakeholders & CONOPs. • Map requirements to payload equipment performance with I/F with on-board processor • Coordinate with cybersecurity team for payload‑specific assessments • Perform requirement management and maintain bidirectional traceability throughout the program life cycle. Payload Architecture & Design • Implement the high‑level digital payload architecture (optical ISLs, Phased array antennas, Feeder links & front‑end), master reference oscillator & clock synchronizations. • Produce Interface Control Documents (ICDs) with other subsystems and ground segment. • Implement high‑speed data‑bus I/F (SpaceWire, SpaceFibre, Ethernet, CAN). Simulation & Analysis • Perform performance simulations (Gain, Spurious, Linearity, SNR, dynamic range, spectral efficiency, G/T, EIRP…etc.) and Monte‑Carlo analyses for tolerance budgeting. • Define and maintain Payload DC power budget with traffic & utilization models • Perform FMECA, Fault tree and FDIR, reliability modeling and availability to meet mission objectives Hardware & Firmware • Provide system‑level specifications to hardware designers, review schematics, layouts, thermal interfaces, and mechanical constraints. • Support SW development for MODCODs and on‑board processing pipelines; ensure BIST, timing, latency and deterministic behavior. Cross‑Functional Coordination, Stakeholder & Program Interaction • Communicate technical status, risk assessments and trade‑study results to senior management and/or customers or partners. • Support payload design authority in System design reviews, Power/Structure/Thermal interfaces and Mission Operations assessments. • Liaise with Electrical, Power, Structures, Thermal, Software, Ground‑Segment and Mission‑Operations teams to resolve integration issues early. • Support B&P (Phase 0 & pre-phase A). Integration & Verification (IVV) • Develop Payload Verification Master Plan covering unit‑test, subsystem‑test, payload‑level test, environmental and electromagnetic compatibility (EMC) test campaigns. • Lead test‑automation framework set‑up, test‑case definition, results analysis and test‑report certification. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to the company’s knowledge‑base, process enhancements, and standards development. Configuration, Documentation & Standards Management • Ensure all artefacts, analysis, software, deliverables and documentation are version controlled in PLM environment. • Lead and Support design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation. On Orbit & Operations Support • Provide technical support to Mission Operations for routine payload health monitoring, contingency handling and performance trending. • Lead root‑cause investigations for on‑orbit anomalies; update design baselines and lessons‑learned. • Analyze on‑orbit telemetry, update filter parameters, and generate performance reports. • Support SOOH development and associated operator training. Required Qualifications:  B.Sc. in Electrical Engineering, Aerospace or Physics with 8 + years of digital regenerative payload system design experience on LEO/MEO missions.  Comprehensive knowledge of digital communications, SDR, DSP, DVB RCS/SX protocols, Modulation schemes, Class of Service, Networking, MPLS, 2G, 5G NTN.  Strong technical-writing ability (requirements, ICDs, test procedures, risk reports) and presentation skills; comfortable interfacing with customers, suppliers and senior leadership.  Strong understanding of aerospace system engineering fundamentals.  Hands-on individual who can support systems integration processes and capability to test systems and resolve problems.  Experience with Confluence and JIRA.  Demonstrated capability to efficiently work with little supervision.  Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity.  Demonstrate excellent written and oral communication skills in English; knowledge of French will be considered an asset (Contact with clients outside Quebec and work on deliverables in English).

Location: Toulouse, France; United States; United Kingdom The company provides full relocation support, including immigration assistance, and offers a relocation bonus upon arrival in Montreal. Selected candidates may work remotely during the initial months while their immigration process is being completed; however, the long-term expectation is for the individual to transition to onsite work in Montreal once relocation has been finalized. Tasks summary: Architecture Concept & Requirements • Establish functional, performance, environmental and security requirements with mission stakeholders & CONOPs. • Translate requirements into clear payload performance parameters and maintain bidirectional traceability throughout the project lifecycle. • Establish with cybersecurity team payload‑specific requirements & embed resilience and security by design. Payload Architecture Definition • Define the overall digital regenerative payload architecture (optical/RF ISLs, antenna arrays, digitizers/ onboard processing, Feeder links, master reference oscillator & clock synchronizations). • Define Interface Control Documents (ICDs) with spacecraft bus, ground segment and payload specific subsystems. • Define high‑speed data‑bus I/F (Serdes, SpaceWire, SpaceFibre, Ethernet, CAN, fiber). Trade‑Study & Technology Road‑Mapping • Lead trade‑offs for technologies, ASIC/FPGAs/SoCs, high‑speed data‑bus, and on‑board processing algorithms, PVT. • Identify emerging technologies and incorporate them into the company’s long‑term roadmap. System Modeling & Performance Simulation • Build end‑to‑end models of the signal chain (optical/RF, analog/digital) using MATLAB/Simulink, SystemView or Python‑based toolkits. • Run Monte‑Carlo and tolerance analyses to verify gain, SNR, dynamic range, spectral efficiency, G/T, EIRP and other key metrics. • Optimize payload design and performance with operation with traffic models/CONOPs. Simulation & Analysis • Oversee performance simulations & analysis (Gain, Spurious, Linearity, SNR, dynamic range, spectral efficiency, pointing, G/T, EIRP…etc.) and tolerance budgeting. • Optimize Payload DC power budget with traffic & utilization models. Hardware & Firmware • Own system‑level specifications to hardware designers, review schematics, layouts, thermal & mechanical interfaces. • Oversee MODCODs selection and on‑board processing pipelines; define BIST, timing, latency and deterministic behavior. Cross‑Functional Coordination, Stakeholder & Program Interaction • Communicate technical status, risk assessments and trade‑study results to senior management and/or customers or partners. • Act as the primary technical liaison with Electrical, Power, Structures, Thermal, Software, Ground Segment and Mission Operations teams to resolve integration issues early. • Support payload design authority in System design reviews and Mission Operations hand‑over. • Support B&P (Phase 0 & pre-phase A). Integration & Verification (IVV) • Author Payload Verification Master Plan covering unit‑test, subsystem‑test, payload‑level test, environmental and electromagnetic compatibility (EMC) test campaigns. • Define test‑automation framework set‑up, test‑case definition, results analysis and test‑report certification. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to the company’s knowledge‑base, process enhancements, and standards development. Configuration, Documentation & Standards Management • Ensure all artefacts, analysis, software, deliverables and documentation are version controlled in PLM environment. • Chair design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation. On Orbit & Operations Support • Technical support to Mission Operations for routine payload health monitoring, contingency handling and performance trending. • Lead root‑cause investigations for on‑orbit anomalies; update design baselines and lessons‑learned. • Analyze on‑orbit telemetry, update filter parameters, and generate performance reports. • Define SOOH and associated operator training. Required Qualifications:  B.Sc. in Electrical Engineering, Aerospace or Physics (M.Sc. preferred) with 12 + years of digital regenerative payload system design experience on LEO/MEO missions.  Comprehensive knowledge of digital regenerative communications, SDR, DSP, DVB RCS/SX protocols, Modulation schemes, Class of Service, Networking, MPLS, 2G, 5G, NTN.  Strong technical writing ability (requirements, ICDs, test procedures, risk reports) and presentation skills; comfortable interfacing with customers, suppliers and senior leadership.  Strong understanding of aerospace system engineering fundamentals.  Hands-on individual who can support systems integration processes and capability to test systems and resolve problems.  Experience with Confluence and JIRA.  Demonstrated capability to efficiently work with little supervision.  Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity.  Demonstrate excellent written and oral communication skills in English; knowledge of French will be considered an asset (Contact with clients outside Quebec and work on deliverables in English).

Location: Toulouse, France; United States; United Kingdom The company provides full relocation support, including immigration assistance, and offers a relocation bonus upon arrival in Montreal. Selected candidates may work remotely during the initial months while their immigration process is being completed; however, the long-term expectation is for the individual to transition to onsite work in Montreal once relocation has been finalized. Tasks summary: Architecture Concept & Requirements • Gather functional, performance, pointing, environmental and security requirements from mission stakeholders & CONOPs. • Capture, trace and map payload requirements from mission level to subsystem level • Coordinate with cybersecurity team for payload‑specific assessments • Perform requirement management and maintain bidirectional traceability throughout the program life cycle. Payload Architecture & Design • Design the SAR system architecture (antenna arrays & RF front-end Tx/Rx components, digital beamforming, processing chain and digital electronics, power, thermal, and mass). • Lead the conceptual, preliminary, and detailed design phases, producing trade studies, performance budgets). • Produce Interface Control Documents (ICDs) with other subsystems and ground segment. • Provide system‑level specifications to hardware designers, review schematics, layouts, thermal interfaces, and mechanical constraints Simulation & Analysis • Perform performance simulations for tolerance budgeting and image quality. • Support algorithm and analytical development to process SAR. • Define and maintain Payload DC power budget with utilization models. • Perform FMECA, Fault tree and FDIR, reliability modeling and availability to meet mission objectives Cross‑Functional Coordination, Stakeholder & Program Interaction • Communicate technical status, risk assessments and trade‑study results to senior management and/or customers or partners. • Support payload design authority in System design reviews, Power/Structure/Thermal interfaces and Mission Operations assessments. • Liaise with Electrical, Power, Structures, Thermal, Software, Ground‑Segment and Mission‑Operations teams to resolve integration issues early. • Support B&P (Phase 0 & pre-phase A). Integration & Verification (IVV) • Develop Payload Verification Master Plan covering unit‑test, subsystem‑test, payload‑level test, environmental and electromagnetic compatibility (EMC) test campaigns. • Lead test‑automation framework set‑up, test‑case definition, results analysis and test‑report certification. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to the company’s knowledge‑base, process enhancements, and standards development. Configuration, Documentation & Standards Management • Ensure all artefacts, analysis, firmware, deliverables and documentation are version controlled in PLM environment. • Lead and Support design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation. On Orbit & Operations Support • Provide technical support to Mission Operations for routine payload health monitoring, contingency handling and performance trending. • Lead root‑cause investigations for on‑orbit anomalies; update design baselines and lessons‑learned. • Analyze on‑orbit telemetry, update filter parameters, and generate performance reports. • Support SOOH development and associated operator training. Required Qualifications:  B.Sc. in Electrical Engineering, Computer science or Physics with 10 + years of experience supporting SAR remote sensing system development, integration and test on LEO/MEO missions.  Strong technical-writing ability (requirements, ICDs, test procedures, risk reports) and presentation skills; comfortable interfacing with customers, suppliers and senior leadership.  Strong understanding of aerospace system engineering fundamentals.  Hands-on individual who can support systems integration processes and capability to test systems and resolve problems.  Experience with Confluence and JIRA.  Demonstrated capability to efficiently work with little supervision.  Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity.  Demonstrate excellent written and oral communication skills in English; knowledge of French will be considered an asset (Contact with clients outside Quebec and work on deliverables in English).

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role 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 10+ 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, latency-sensitive systems Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.) Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software 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: $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.

Location: Montreal, Canada The company offers full relocation support , including immigration assistance. Tasks: The Junior FDIR-FSW Engineer will perform and participate in the following tasks and activities, depending on the background and experience of the candidate. · Document the fault detection actions of the platform and payload at the system and subsystem levels. · Work with system, subsystem, payload and unit teams to review FMECAs and provide feedback on the detection, isolation, and recovery of failures modes. · Provide input to the Operations team for Operations Procedures, Operations Manuals, and Satellite test procedures to ensure that the Operations documents and FDIR strategy are aligned. · Review ICDs to provide inputs to the satellite DB team for parameters and monitors. · Review payload, platform, and subsystem design and requirements to ensure that the design is compliant with FDIR requirements. · Review Operations Procedures to ensure that they algin with the FDIR strategy. · Review FDIR test artifacts to determine if the tests are successful. · Verification & Validation Matrices for payload and platform FDIR requirements. · Support the operations team as needed for In-Orbit Test (IOT), anomaly resolution + FDIR. · Support the payload team for definition of payload to platform FDIR. · Support the ICD development activities both HW and SW/DB Must haves · Bachelor’s degree in electrical engineering, computer science or in a relevant field · At least 5 years of relevant practical experience – Can be supplemented with higher degrees relevant to Engineering. · Knowledge of LEO/MEO satellite systems. · Knowledge of satellite systems and subsystems. Complementary skills/knowledge · Previous experience in Constellation FDIR · Creation of Fault Trees and FMECAs · Working knowledge of PUS services · Experience and/or development of payloads · Knowledge of MS Excel, for the purposes of engineering analyses · Strong written and verbal communications skills in English, knowledge of French will be considered favorably

Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. Decisions in production training depend on knowing how the model is really behaving. Our team's mission is to have the best observability into production post-training runs at Anthropic: to be the clearest, most trusted view of model quality during training. We shape what gets measured, keep the signal trustworthy and timely, and get to the bottom of surprising results to inform post-training and release decisions. In this role you will lead the science of how we evaluate production training runs. You'll work out which measurements tell us something real about the model, notice when they stop doing so, and find what we should be measuring but aren't. You'll partner with research teams across every RL domain, bringing their priorities into what we measure and setting the standard for what makes an eval trustworthy across post-training. You'll also be hands-on with the eval fleet day to day, because the best questions about measurement come from watching real results come in during a live run. Responsibilities Steer the eval strategy for production Claude models: study and optimize the eval mix so it gives the most accurate and complete assessment of model quality Run and monitor the eval fleet live to understand how each Claude model is developing as it trains Advise teams across post-training on eval methodology, and help eval authors bring new evals up to the bar for production Investigate regressions in production runs and inform training interventions when appropriate Build the dashboards, alerts, and reports that researchers and leadership use to track model quality You may be a good fit if you Have designed, run, and analyzed evaluations for ML models at scale Care deeply about measurement quality, thinking twice before trusting a number Can turn ambiguous results into clear recommendations, and are comfortable influencing direction across teams Have strong Python skills and are comfortable working with production systems Maintain clarity and rigor when debugging complex, time-sensitive issues Thrive in controlled chaos and are energized, rather than overwhelmed, when juggling multiple urgent priorities during a live training run Care about the societal impacts of your work and about shipping frontier models responsibly Strong candidates may also have Hands-on experience post-training large language models Research experience in ML evaluation or benchmarking Background in statistics and experimental design Experience developing robust evaluation metrics for ML 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: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Montreal, Canada The company offers full relocation support , including immigration assistance. Tasks: The Senior FDIR-FSW Engineer will perform and participate in the following tasks and activities, depending on the background and experience of the candidate. · Define the fault detection actions of the platform at the system and subsystem levels. · Define and document how the platform will interfact with the payload for satellite level FDIR. · Work with the operations team to define the contingency scenarios involving FDIR. · Work with customers to use their input for FDIR strategy to refine MDA’s FDIR strategy ensuing that the strategies are compatible. · Work with the FSW team to determine the FDIR test plan on the FlatSat and DSS. · Work with the AI&T team to determine what FDIR needs to be tested at the spacecraft level. · Work with system, subsystems, payload, and units teams to review FMECAs and provide feedback on the detection, isolation, and recovery of failures modes. · Provide input to the Operations team for Operations Procedures, Operations Manuals, and Satellite test procedures to ensure that the Operations documents and FDIR strategy are aligned. · Review ICDs to provide inputs to the satellite DB team for parameters and monitors. · Review payload, platform, and subsystem design; including block diagrams, ICDs, ConOps, and requirement to ensure that the design is compliant with FDIR requirements. · Review Operations Procedures to ensure that they algin with the FDIR strategy. · Review FDIR test artifacts to determine if the tests are successful and if they are not, work with the team to troubleshoot how to resolve non compliances. · Verification & Validation Matrices for platform and payload FDIR requirements. · Support the payload team in their definition of payload FDIR and how it impacts the satellite level FDIR. · Support the operations team as needed for In-Orbit Test (IOT), anomaly resolution + FDIR. · Support the ICD development activities both HW and SW/DB Must haves · Bachelor’s degree in electrical engineering, computer science or in a relevant field · At least 10 years of relevant practical experience – Can be supplemented with higher degrees relevant to Engineering. · Previous experience with LEO/MEO satellite systems. · Strong cross-functional team collaboration. · Experience with analysis of satellite systems and subsystems. · Familiarity and/or experience with FMECAs and/or Fault Tree Analysis. · An understanding of how failures can propagate through a system. · Ability to decompose system level failures down to the unit level and back up from the unit to the system level. · Knowledge of satellite FSW and how monitors work for FDIR. · Knowledge of how to test HW and SW for FDIR. Complementary skills/knowledge · Previous experience in Constellation FDIR · Creation of Fault Trees and FMECAs · Experience with reliability analysis · Working knowledge of PUS services · Experience with mentoring junior engineers · Experience with FDIR on embedded systems · Experience with payload FDIR. · Knowledge of MS Excel, for the purposes of engineering analyses · Knowledge of requirements Management tools such as DOORS/Windchill/Jama · Demonstrated capability to efficiently work with little to no supervision · Strong written and verbal communications skills in English, knowledge of French will be considered favorably

Location: Montreal, Canada The company provides full relocation support, including immigration assistance, and offers a relocation bonus upon arrival in Montreal. Selected candidates may work remotely during the initial months while their immigration process is being completed; however, the long-term expectation is for the individual to transition to onsite work in Montreal once relocation has been finalized. Tasks summary: Architecture Concept & Requirements • Establish functional, performance, environmental and security requirements with mission stakeholders & CONOPs. • Translate requirements into clear payload performance parameters and maintain bidirectional traceability throughout the project lifecycle. • Establish with cybersecurity team payload‑specific requirements & embed resilience and security by design. Payload Architecture Definition • Define the overall digital regenerative payload architecture (optical/RF ISLs, antenna arrays, digitizers/ onboard processing, Feeder links, master reference oscillator & clock synchronizations). • Define Interface Control Documents (ICDs) with spacecraft bus, ground segment and payload specific subsystems. • Define high‑speed data‑bus I/F (Serdes, SpaceWire, SpaceFibre, Ethernet, CAN, fiber). Trade‑Study & Technology Road‑Mapping • Lead trade‑offs for technologies, ASIC/FPGAs/SoCs, high‑speed data‑bus, and on‑board processing algorithms, PVT. • Identify emerging technologies and incorporate them into the company’s long‑term roadmap. System Modeling & Performance Simulation • Build end‑to‑end models of the signal chain (optical/RF, analog/digital) using MATLAB/Simulink, SystemView or Python‑based toolkits. • Run Monte‑Carlo and tolerance analyses to verify gain, SNR, dynamic range, spectral efficiency, G/T, EIRP and other key metrics. • Optimize payload design and performance with operation with traffic models/CONOPs. Simulation & Analysis • Oversee performance simulations & analysis (Gain, Spurious, Linearity, SNR, dynamic range, spectral efficiency, pointing, G/T, EIRP…etc.) and tolerance budgeting. • Optimize Payload DC power budget with traffic & utilization models. Hardware & Firmware • Own system‑level specifications to hardware designers, review schematics, layouts, thermal & mechanical interfaces. • Oversee MODCODs selection and on‑board processing pipelines; define BIST, timing, latency and deterministic behavior. Cross‑Functional Coordination, Stakeholder & Program Interaction • Communicate technical status, risk assessments and trade‑study results to senior management and/or customers or partners. • Act as the primary technical liaison with Electrical, Power, Structures, Thermal, Software, Ground Segment and Mission Operations teams to resolve integration issues early. • Support payload design authority in System design reviews and Mission Operations hand‑over. • Support B&P (Phase 0 & pre-phase A). Integration & Verification (IVV) • Author Payload Verification Master Plan covering unit‑test, subsystem‑test, payload‑level test, environmental and electromagnetic compatibility (EMC) test campaigns. • Define test‑automation framework set‑up, test‑case definition, results analysis and test‑report certification. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to the company’s knowledge‑base, process enhancements, and standards development. Configuration, Documentation & Standards Management • Ensure all artefacts, analysis, software, deliverables and documentation are version controlled in PLM environment. • Chair design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation. On Orbit & Operations Support • Technical support to Mission Operations for routine payload health monitoring, contingency handling and performance trending. • Lead root‑cause investigations for on‑orbit anomalies; update design baselines and lessons‑learned. • Analyze on‑orbit telemetry, update filter parameters, and generate performance reports. • Define SOOH and associated operator training. Required Qualifications:  B.Sc. in Electrical Engineering, Aerospace or Physics (M.Sc. preferred) with 12 + years of digital regenerative payload system design experience on LEO/MEO missions.  Comprehensive knowledge of digital regenerative communications, SDR, DSP, DVB RCS/SX protocols, Modulation schemes, Class of Service, Networking, MPLS, 2G, 5G, NTN.  Strong technical writing ability (requirements, ICDs, test procedures, risk reports) and presentation skills; comfortable interfacing with customers, suppliers and senior leadership.  Strong understanding of aerospace system engineering fundamentals.  Hands-on individual who can support systems integration processes and capability to test systems and resolve problems.  Experience with Confluence and JIRA.  Demonstrated capability to efficiently work with little supervision.  Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity.  Demonstrate excellent written and oral communication skills in English; knowledge of French will be considered an asset (Contact with clients outside Quebec and work on deliverables in English).

Location: Montreal, Canada The company provides full relocation support, including immigration assistance, and offers a relocation bonus upon arrival in Montreal. Selected candidates may work remotely during the initial months while their immigration process is being completed; however, the long-term expectation is for the individual to transition to onsite work in Montreal once relocation has been finalized. Tasks summary: Architecture Concept & Requirements • Gather functional, performance, environmental and security requirements from mission stakeholders & CONOPs. • Map requirements to payload equipment performance with I/F with on-board processor • Coordinate with cybersecurity team for payload‑specific assessments • Perform requirement management and maintain bidirectional traceability throughout the program life cycle. Payload Architecture & Design • Implement the high‑level digital payload architecture (optical ISLs, Phased array antennas, Feeder links & front‑end), master reference oscillator & clock synchronizations. • Produce Interface Control Documents (ICDs) with other subsystems and ground segment. • Implement high‑speed data‑bus I/F (SpaceWire, SpaceFibre, Ethernet, CAN). Simulation & Analysis • Perform performance simulations (Gain, Spurious, Linearity, SNR, dynamic range, spectral efficiency, G/T, EIRP…etc.) and Monte‑Carlo analyses for tolerance budgeting. • Define and maintain Payload DC power budget with traffic & utilization models • Perform FMECA, Fault tree and FDIR, reliability modeling and availability to meet mission objectives Hardware & Firmware • Provide system‑level specifications to hardware designers, review schematics, layouts, thermal interfaces, and mechanical constraints. • Support SW development for MODCODs and on‑board processing pipelines; ensure BIST, timing, latency and deterministic behavior. Cross‑Functional Coordination, Stakeholder & Program Interaction • Communicate technical status, risk assessments and trade‑study results to senior management and/or customers or partners. • Support payload design authority in System design reviews, Power/Structure/Thermal interfaces and Mission Operations assessments. • Liaise with Electrical, Power, Structures, Thermal, Software, Ground‑Segment and Mission‑Operations teams to resolve integration issues early. • Support B&P (Phase 0 & pre-phase A). Integration & Verification (IVV) • Develop Payload Verification Master Plan covering unit‑test, subsystem‑test, payload‑level test, environmental and electromagnetic compatibility (EMC) test campaigns. • Lead test‑automation framework set‑up, test‑case definition, results analysis and test‑report certification. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to the company’s knowledge‑base, process enhancements, and standards development. Configuration, Documentation & Standards Management • Ensure all artefacts, analysis, software, deliverables and documentation are version controlled in PLM environment. • Lead and Support design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation. On Orbit & Operations Support • Provide technical support to Mission Operations for routine payload health monitoring, contingency handling and performance trending. • Lead root‑cause investigations for on‑orbit anomalies; update design baselines and lessons‑learned. • Analyze on‑orbit telemetry, update filter parameters, and generate performance reports. • Support SOOH development and associated operator training. Required Qualifications:  B.Sc. in Electrical Engineering, Aerospace or Physics with 8 + years of digital regenerative payload system design experience on LEO/MEO missions.  Comprehensive knowledge of digital communications, SDR, DSP, DVB RCS/SX protocols, Modulation schemes, Class of Service, Networking, MPLS, 2G, 5G NTN.  Strong technical-writing ability (requirements, ICDs, test procedures, risk reports) and presentation skills; comfortable interfacing with customers, suppliers and senior leadership.  Strong understanding of aerospace system engineering fundamentals.  Hands-on individual who can support systems integration processes and capability to test systems and resolve problems.  Experience with Confluence and JIRA.  Demonstrated capability to efficiently work with little supervision.  Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity.  Demonstrate excellent written and oral communication skills in English; knowledge of French will be considered an asset (Contact with clients outside Quebec and work on deliverables in English).

Location: Montreal, Canada The company provides full relocation support, including immigration assistance, and offers a relocation bonus upon arrival in Montreal. Selected candidates may work remotely during the initial months while their immigration process is being completed; however, the long-term expectation is for the individual to transition to onsite work in Montreal once relocation has been finalized. Tasks summary: Architecture Concept & Requirements • Gather functional, performance, pointing, environmental and security requirements from mission stakeholders & CONOPs. • Capture, trace and map payload requirements from mission level to subsystem level • Coordinate with cybersecurity team for payload‑specific assessments • Perform requirement management and maintain bidirectional traceability throughout the program life cycle. Payload Architecture & Design • Design the SAR system architecture (antenna arrays & RF front-end Tx/Rx components, digital beamforming, processing chain and digital electronics, power, thermal, and mass). • Lead the conceptual, preliminary, and detailed design phases, producing trade studies, performance budgets). • Produce Interface Control Documents (ICDs) with other subsystems and ground segment. • Provide system‑level specifications to hardware designers, review schematics, layouts, thermal interfaces, and mechanical constraints Simulation & Analysis • Perform performance simulations for tolerance budgeting and image quality. • Support algorithm and analytical development to process SAR. • Define and maintain Payload DC power budget with utilization models. • Perform FMECA, Fault tree and FDIR, reliability modeling and availability to meet mission objectives Cross‑Functional Coordination, Stakeholder & Program Interaction • Communicate technical status, risk assessments and trade‑study results to senior management and/or customers or partners. • Support payload design authority in System design reviews, Power/Structure/Thermal interfaces and Mission Operations assessments. • Liaise with Electrical, Power, Structures, Thermal, Software, Ground‑Segment and Mission‑Operations teams to resolve integration issues early. • Support B&P (Phase 0 & pre-phase A). Integration & Verification (IVV) • Develop Payload Verification Master Plan covering unit‑test, subsystem‑test, payload‑level test, environmental and electromagnetic compatibility (EMC) test campaigns. • Lead test‑automation framework set‑up, test‑case definition, results analysis and test‑report certification. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to the company’s knowledge‑base, process enhancements, and standards development. Configuration, Documentation & Standards Management • Ensure all artefacts, analysis, firmware, deliverables and documentation are version controlled in PLM environment. • Lead and Support design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation. On Orbit & Operations Support • Provide technical support to Mission Operations for routine payload health monitoring, contingency handling and performance trending. • Lead root‑cause investigations for on‑orbit anomalies; update design baselines and lessons‑learned. • Analyze on‑orbit telemetry, update filter parameters, and generate performance reports. • Support SOOH development and associated operator training. Required Qualifications:  B.Sc. in Electrical Engineering, Computer science or Physics with 10 + years of experience supporting SAR remote sensing system development, integration and test on LEO/MEO missions.  Strong technical-writing ability (requirements, ICDs, test procedures, risk reports) and presentation skills; comfortable interfacing with customers, suppliers and senior leadership.  Strong understanding of aerospace system engineering fundamentals.  Hands-on individual who can support systems integration processes and capability to test systems and resolve problems.  Experience with Confluence and JIRA.  Demonstrated capability to efficiently work with little supervision.  Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity.  Demonstrate excellent written and oral communication skills in English; knowledge of French will be considered an asset (Contact with clients outside Quebec and work on deliverables in English).

Location: London, UK 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 RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities Build and improve the RL training infrastructure that researchers depend on day-to-day Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster Own the reliability and performance of research runs end-to-end Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you Have strong software engineering fundamentals and a track record of building performant, reliable systems Have worked on ML infrastructure, distributed systems, or research tooling Care about enabling other people's work and find leverage through platforms rather than individual experiments Are comfortable operating across the stack, from low-level performance work to RL algorithms Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have Experience with large-scale distributed training (RL, pre-training, or post-training) Familiarity with JAX, PyTorch, or similar ML frameworks A track record of operating at the edge of research and infra in a fast-moving environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £370,000 — £630,000 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.

Location: Remote-Friendly (Travel-Required) | San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities Build and improve the RL training infrastructure that researchers depend on day-to-day Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster Own the reliability and performance of research runs end-to-end Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you Have strong software engineering fundamentals and a track record of building performant, reliable systems Have worked on ML infrastructure, distributed systems, or research tooling Care about enabling other people's work and find leverage through platforms rather than individual experiments Are comfortable operating across the stack, from low-level performance work to RL algorithms Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have Experience with large-scale distributed training (RL, pre-training, or post-training) Familiarity with JAX, PyTorch, or similar ML frameworks A track record of operating at the edge of research and infra in a fast-moving environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York City, NY; Remote-Friendly (Travel-Required) | San Francisco, CA | Washington, DC; San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic sits at the frontier of AI development, which makes us one of the most interesting targets in the world for nation-state and advanced criminal actors. The Threat Intelligence function within our Detection & Response team exists to make sure we see them coming. As a Threat Intelligence Engineer, you'll be a hands-on practitioner responsible for producing the actionable intelligence that drives our detections, hunts, and defensive priorities. You'll track the adversaries most likely to target a frontier AI lab, build the tooling and pipelines that turn raw indicators into operational defenses, and work shoulder-to-shoulder with detection engineers and incident responders to make sure intelligence actually changes outcomes. This is a builder's role on a small, high-leverage team — you'll have broad latitude to shape how threat intelligence is collected, analyzed, and operationalized at Anthropic. Responsibilities: Research, track, and report on threat actors and campaigns targeting AI labs, cloud infrastructure, and the broader technology sector — producing timely, actionable intelligence for Security Engineering stakeholders Build and maintain tooling and automated pipelines to collect, enrich, correlate, and operationalize indicators of compromise into our detection and alerting stack Develop and execute intelligence-driven threat hunts across endpoint, cloud, identity, and SaaS telemetry, and turn findings into durable detections Perform technical analysis of malware, phishing infrastructure, and attacker tooling to extract indicators, TTPs, and attribution signals Partner with Detection Engineering and Incident Response to translate intelligence into detection rules, hunting hypotheses, and incident context in near-real-time Curate and triage inbound intelligence from commercial feeds, open source, government, and trusted peer relationships — prioritizing what matters for Anthropic's threat model Contribute to threat models and risk assessments that inform security architecture and defensive investment across the enterprise Build and maintain external intelligence-sharing relationships with peer companies, ISACs, and government partners You may be a good fit if you: Have 5+ years of hands-on experience in cyber threat intelligence, threat hunting, or intrusion analysis at an organization facing sophisticated adversaries Have deep, demonstrable knowledge of specific nation-state or advanced criminal threat actors — their tooling, infrastructure patterns, tradecraft, and targeting Are a strong engineer: you write production-quality Python (or similar), have built automation and data pipelines, and don't need to hand requirements to someone else to get tooling built Are comfortable performing malware analysis, infrastructure analysis (passive DNS, certificate pivoting, netflow), and log analysis to develop and validate your own findings Have experience authoring detection logic (YARA, Sigma, Snort/Suricata, or SIEM-native queries) and understand what makes a detection durable vs. brittle Can write clearly and concisely — your intelligence products are read and acted on, not filed away Have an existing network in the threat intelligence community and a track record of productive bidirectional sharing Strong candidates may have: Experience defending cloud-native and research-heavy environments (AWS/GCP, Kubernetes, ML infrastructure, developer tooling and supply chain) Prior work operating in a threat intelligence role tracking sophisticated or state-sponsored adversaries, where your analysis directly informed detection, threat hunting, and incident response Experience applying LLMs or other AI tooling to accelerate intelligence collection, enrichment, and analysis Public research, conference talks, or open-source tooling contributions in the CTI space Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $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.