Technical Program Manager, Model Evaluations

About the Role

As a Technical Program Manager for model evaluations, you'll own end-to-end coordination of our evaluation ecosystem— building a feedback loop from shaping eval strategy during early model development through launch execution. You'll be the critical bridge between Research, Product, Marketing, and Engineering teams.

This role sits at the intersection of frontier AI research and product launches. Evals are an important part of how we measure whether our models meet the bar—for capability, safety, and competitive positioning. Beyond launch coordination, you'll help scale our evals ecosystem: from early-stage model evals for RL environments, to the systems and infrastructure on which evals run, to tooling that enables the whole pipeline. A strong TPM in this space can immediately reduce chaos during launches while also driving systemic improvements that compound over time.

Key Responsibilities:

Launch Coordination

• Standardize how evaluation results are generated, documented, compared across model versions, and communicated to stakeholders
• Own end-to-end eval readiness for model launches—tracking which evals are ready, which need scores on past models, and which meet the bar for marketing materials
• Establish and enforce clear criteria for eval inclusion: scores on historical models, state-of-the-art performance, and competitor comparisons
• Coordinate between research teams, marketing, and product to consolidate eval status into a single source of truth
• Maintain a high bar: ensure reported statistics reflect model capabilities in an honest, accurate, and transparent way

Ecosystem Development

• Get involved early in model development cycles, helping shape eval plans for RL environments
• Partner with research and infrastructure teams to improve underlying evals infrastructure—eval-syncer reliability, results storage and querying, automation capabilities
• Drive prioritization of eval tooling enhancements based on researcher needs
• Identify patterns across launches and drive systemic fixes rather than point solutions
• Work with PMs and researchers to improve and implement high priority evals launches
• Maintain and prioritize the eval roadmap—working with cross-functional teams to identify which new evals are needed for upcoming launches and product requirements
• Implement an operating model that reflects an evals environment with increasing complexity

Process & Systems

• Build lightweight but rigorous tracking systems—moving key information into structured formats that enable better decision-making
• Create eval dashboards that provide real-time visibility into training progress on hero evals, enabling earlier intervention when scores look concerning
• Document eval processes, requirements, and lessons learned to build institutional knowledge
• Coordinate compute allocation for large-scale evals with infrastructure teams

You May Be a Good Fit If You:

• Have 5+ years of technical program management experience with a track record of bringing order to chaotic, high-stakes coordination problems
• Possess scientific depth and a very high quality bar for data
• Have experience with ML/AI evaluation methodologies, benchmarking, or research quality assurance
• Have a background in research operations, scientific publishing, or data quality management
• Have previous experience as data analyst, data scientist, or software engineer
• Can build trust with research teams by understanding their work deeply enough to add value beyond coordination
• Are skilled at cross-functional coordination involving research, product, marketing, and engineering—navigating competing priorities and driving alignment
• Have working familiarity with data analysis tools (SQL, Python, or similar) for querying eval results and building dashboards
• Have familiarity with LLM capabilities and limitations and experience working with AI research teams
• Excel at written and verbal communication, translating technical nuance for marketing stakeholders while maintaining precision
• Thrive in unstructured environments with a bias toward action and a knack for creating clarity in ambiguous situations
• Have extremely high ownership and attention to detail

Deadline to apply: None, applications will be received on a rolling basis.