Head of Research

Responsibilities

• Own the research agenda for building a replayable environment engine over real enterprise history.
• Identify high-leverage technical questions and design experiments to answer them.
• Build systems that convert recorded enterprise data and task definitions into runnable environments.
• Design graders that turn ambiguous business objectives into verifiable rewards.
• Mine useful tasks, trajectories, and evaluation cases from historical workflows.
• Create representative, reproducible, and overfitting-resistant evaluation sets.
• Determine effective combinations of models, tools, context, and policies while reducing inference cost.
• Advance post-training methods for agents operating over long horizons, incomplete information, and large tool spaces.
• Build replay and observability systems that make agent behavior explainable and measurable.
• Scale to thousands of concurrent training and evaluation runs.
• Help establish research practices, evaluate technical progress, select research bets, and recruit and develop the research team.
• Collaborate directly with the CTO and deploy research into enterprise workflows.

Requirements

• PhD in machine learning, computer science, mathematics, or equivalent significant research experience.
• Deep experience in reinforcement learning, LLM post-training, evaluations, agent environments, or closely related areas.
• Experience taking ambitious, open-ended research problems from hypothesis through experimentation to working systems.
• Ability to turn ambiguous business objectives into reliably evaluable tasks and signals.
• Ability to move between research and production implementation.

Nice-to-haves

• Experience at a leading foundation model lab, top AI research organization, or high-performing AI startup.

Compensation and Benefits

• Salary: $250,000–$400,000 per year.
• Significant equity and ownership.
• Equinox membership.
• Free meals, coffee, and snacks.
• Health insurance.
• Unlimited PTO.