Technical Program Manager, RL Research

Anthropics 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.

Our Reinforcement Learning teams are central to advancing our AI systems contributing to every Claude model and driving the autonomy and coding gains in our latest releases. The work spans computer use code generation through RL fundamental RL research for large language models scalable infrastructure and training methodologies and model reasoning.

Research TPM team supports the full model development lifecycle from pre-training through post-training operating at the frontier of AI development.

As a Technical Program Manager on the reinforcement learning team you will own the systems and programs that determine how fast our research moves: a trustworthy read on the state of RL research the review and prioritization processes that turn that read into critical decision for production RL runs. Strong candidates should have an ML engineering or research background and have grown into program leadership. Youll need real technical depth: the ability to debug data pipelines read RL transcripts to spot issues and make allocation and quality decisions in real time when research or production runs hit problems. Youll need organizational effectiveness in equal measure: the ability to navigate a fast-growing organization quickly identify the critical people and teams across research infrastructure product and data operations and coordinate across them without losing velocity.

Join us in our mission to build AI systems that are safe reliable and beneficial to humanity.

• Deliver a regular read on the ground truth in RL research covering performance against baselines experiment results day-to-day health and incidents
• Work with RL org leads on prioritizing ranking and tracking the state of experiments
• Drive research reviews end to end in partnership with set the agenda make sure the right context is in the room ahead of time and close the loop on what gets decided
• Establish processes and frameworks that bring structure to an unstructured research setting without slowing researchers down
• Collaborate with research leads infrastructure engineers and data operations to identify blockers prioritize competing needs and make technical trade-off decisions

• Have a background in ML engineering or ML research before transitioning to technical program management
• Have deep hands-on experience with ML training pipelines RLHF systems and large-scale data infrastructure in production
• Have a track record of building execution plans and inventing high-leverage processes that reduce operational overhead and let researchers focus on research
• Are a fast learner who builds deep contextual understanding in unfamiliar technical domains and can contribute meaningfully to discussions with researchers
• Are resourceful high-agency and able to navigate ambiguity and shifting priorities to drive progress in a fast-moving research setting
• Have excellent stakeholder management and communication skills with the ability to influence senior technical staff through clarity competence and consistent delivery
• Are excited about pushing the frontier of what RL can do at scale

Minimum education: Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 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 youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

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. Were 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.

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 aboutour policy for using AI in our application process.