Technical Program Manager (Research)

• 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
• 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

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents

• Inclusive fertility benefits via Carrot Fertility

• 22 weeks of paid parental leave

• Flexible paid time off and absence policies

• Mental health support for you and your dependents

• Competitive salary and equity packages

• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant

• Retirement plans with competitive matching

• Life and income protection plans

• $500/month flexible wellness and time saver stipend

• Commuter benefits

• Annual education stipend

• Home office stipends

• Relocation support for those moving for Anthropic

• Daily meals and snacks in the office

• 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

• 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 resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in fast-moving research environments

• Are comfortable with high-stakes environments where decisions impact compute spend, model training timelines, and launch outcomes

• Are a fast learner who can ramp on unfamiliar technical domains quickly and contribute meaningfully to discussions with researchers

• Have a track record of operational ownership of complex technical systems, including monitoring, incident response, and performance optimization

• Have excellent stakeholder management skill and the ability to influence senior technical staff through competence and consistent delivery

• Can reason about technical tradeoffs at depth across model architecture, training infrastructure, evals, or compute efficiency, and translate them into clear decisions for leadership

• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

• 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

• 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