About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Team
The Discovery team is organized around the north star of building an AI scientist — a system capable of solving the long-horizon reasoning challenges and core capabilities needed to push the scientific frontier. The team trains large-scale models, runs complex multi-week experiments, and builds novel products at the intersection of AI and science.
About the Role
As a Technical Program Manager on the Discovery team, you will own the systems and programs that determine how fast our research moves: compute planning, scientific RL environment health, and the vendor pipelines that supply them, with scope to incubate new programs in domains like bio R&D. Strong candidates should have an ML engineering or research background and have grown into program leadership. You'll 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 experimental or production runs hit problems. You'll 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 push the frontiers of science and benefit humanity.
Responsibilities
- Manage Discovery's compute planning across supervised learning (SL), reinforcement learning (RL), and sandboxing workloads, including forecasting, allocation, prioritization, and efficiency improvements. Partner with central compute planning to ensure Discovery's needs are represented and met.
- Monitor the health of scientific RL environments (quality, reward integrity, failure rates) and drive issues to resolution.
- Expedite the external vendor pipeline for RL environments, including quality review, reward design, and production integration.
- Work with research teams across life sciences, STEM, and other scientific domains to translate research goals into roadmaps that advance AI scientist capabilities.
- 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.
You May Be a Good Fit If You:
- Have a background in ML engineering, ML research, or STEM R&D 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 the potential for AI to accelerate scientific discovery
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