Technical Program Manager, Research

FAR.AI is a non-profit AI research institute working to ensure advanced AI is safe and beneficial for everyone. Our mission is to facilitate breakthrough AI safety research, advance global understanding of AI risks and solutions, and foster a coordinated global response.

Since our founding in July 2022, we've grown to 45+ staff, published 40+ academic papers including an ICML 2026 Outstanding Paper Honorable Mention, and convened leading AI safety events. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML, and ICLR, and features in the Financial Times, Nature News and MIT Technology Review. We conduct pre-deployment testing on behalf of frontier developers such as OpenAI and independent evaluations for governments including the EU AI Office. We help steer and grow the AI safety field through developing research roadmaps with renowned researchers such as Yoshua Bengio; running FAR.Labs, an AI safety-focused co-working space in Berkeley housing 40 members; and supporting the community through targeted grants to technical researchers.

FAR.AI conducts research to address fundamental artificial intelligence (AI) safety challenges. We rapidly explore a diverse portfolio of technical research agendas, de-risking and scaling up only the most promising solutions. We share our research outputs through peer-reviewed publications, via partnerships with governmental AI safety institutes, and through red-teaming engagements for leading AI companies.

FAR.Research is dedicated to delivering the novel technical breakthroughs needed to mitigate the potential risks posed by frontier AI. As a non-profit research institute, we leverage our unique flexibility to focus on critical research directions that may be too large or resource-intensive for academia and often overlooked by the commercial sector due to their lack of immediate profitability.

We are looking for Technical Program Managers to define programs for both our foundational research and research infrastructure teams. Our Research organization is scaling up by expanding our portfolio of research agendas, including model deception, applied interpretability, evaluation awareness, pre-training filtering, and open-weight safety. As our Research portfolio expands, our Research Infrastructure needs will also scale up to meet these needs. You'll find the highest-leverage problems and own them end to end, building the processes, systems, and tooling that help our researchers and engineers move faster.

• Take complex technical programs from idea to delivery: scope the plan and milestones, then keep complex, multi-team work moving efficiently, transparently, and to a high technical bar.

• Prioritize across competing demands in partnership with research teams so the teams’ effort lands on the highest-impact work.

• Build and maintain compute and resource roadmaps by surfacing bottlenecks and trade-offs, finding ways to accelerate progress and build relationships with potential external partners.

• Partner with researchers to package their work effectively to get our research into the hands of people who can act on it by transferring findings, methods, and tools to frontier labs and other stakeholders.

• Connect research and engineering with our internal partners in Operations, Events and Communications giving each the timelines, results, and context they need to plan, resource, and communicate our work.

This role is a great fit if you

• Are a fast learner and comfortable with ramping up quickly on unfamiliar technical domains to hold your own in discussions with researchers and engineers.

• Can reason about technical trade-offs in depth (e.g. measuring quality of agent output balanced against credit spend, compute efficiency, and training and inference infrastructure) to facilitate clear decisions by stakeholders.

• Enjoy 0-to-1 work by building the processes, systems, and structure where none exist, rather than inheriting them.

• Thrive in an ambiguous, fast-paced environment that is scaling quickly.

• Hold a deep commitment to ensuring safe and beneficial AI.

This role is a poor fit if you

• Have no technical background. You don't need to code, but you do need to understand AI/ML well enough to hold your own in discussions with researchers and follow the substance of the work.

• Want to inherit a mature TPM function rather than help build one.

• Are looking for a product management role with a product roadmap, rather than driving programs, processes, and delivery across research and infrastructure.

Strong candidates typically have many (but not all) of the following skills:

• A strong technical background, either in ML, software engineering, or another scientific or research field, with 4+ years building technical programs from scratch

• Practical domain experience in AI/ML such as coordinating model releases, procuring or managing datasets, or supporting evaluations

• A track record of delivering complex technical programs while managing tradeoffs and strategic priorities

• Have successfully facilitated technology transfer of foundational and applied research into production environments

• Strong communication and stakeholder management skills

It is a plus (but not required) if you have experience with:

• Scientific computing cluster management

• Public storytelling through interactive demos or blog posts

• Supporting hiring processes for technical staff

If based in the USA, you will be an employee of FAR.AI (501(c)(3) research non-profit / non-profit CLG). Outside the USA, you will be employed via an EOR organization (employment contract) on behalf of FAR.AI or as a contractor.

• Location: Remote U.S. or Bay Area in-office. We can sponsor US visas.

• Hours: Full-time. 10% travel may be required.

• Compensation: USD 125,000–190,000, depending on experience. Exceptional candidates may be offered more.

If you're uncertain whether your background fits but are excited by the mission and challenges, we encourage you to apply – we're looking for excellence and potential, not a perfect resume match.