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 be embedded in a research domain, charged with understanding how researchers work and what they need, from compute resources to cross-team coordination. 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 a domain, determine what it needs, and create lasting impact where none existed before.
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
- 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
- Coordinate large-scale compute resource planning including allocation, efficiency, and prioritization across research and production workstreams
- 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
- Are a fast learner, capable of understanding and contributing to discussions on complex technical topics
- 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 production ML 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
- Are comfortable with high-stakes environments where decisions impact millions of dollars in compute spend and model training timelines
- 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
Deadline to apply: None, applications will be received on a rolling basis.
