Head of Research & Enterprise AI Systems

Ambral Labs; San Francisco (CA); Sur place; USD 250 000 - 380 000; Plein temps

Avantages offerts par ce poste

Equity

Equinox membership

Free meals

Health insurance

Unlimited PTO

Résumé du poste

Ambral Labs is hiring a Head of Research to lead the research agenda behind our replayable enterprise history environments. You will identify high-leverage questions, design experiments, and stay hands-on building the systems that turn findings into production.

You’ll work closely with the CTO, deploy into real workflows, and shape the research culture as we scale. Ideal candidates possess a PhD in ML, deep RL/post-training experience, and a proven ability to move from hypothesis to deployed

Qualifications

• PhD in machine learning, CS, math, or equivalent research track.
• Deep experience in reinforcement learning, LLM post-training, evals, agent environments, or related areas
• Proven track record turning ambitious, open-ended research problems into working systems
• Comfort turning fuzzy business objectives into measurable tasks and signals
• Ability to move between research questions and production implementation

Responsabilités

• Own the research agenda required to advance the replayable environment engine
• Identify high-leverage technical questions and design experiments to answer them
• Remain hands-on building systems that translate research into production
• Collaborate with CTO and production teams to deploy research into enterprise workflows
• Help establish the research culture and recruit/develop the team
• Scale research output to thousands of concurrent training/evaluation runs

Connaissances

Reinforcement learning

LLM post-training

Experiment design

Production deployment

Formation

PhD in machine learning

Outils

Python

PyTorch

RL frameworks

Description du poste

Ambral Labs is hiring a Head of Research to lead the research agenda behind our replayable enterprise history environments. You will identify high-leverage questions, design experiments, and stay hands-on building the systems that turn findings into production.

You’ll work closely with the CTO, deploy into real workflows, and shape the research culture as we scale. Ideal candidates possess a PhD in ML, deep RL/post-training experience, and a proven ability to move from hypothesis to deployed