Applied Research - Forward-Deployed

Highlights

• Embed with top AI labs to turn agent workflows into production RL training runs.
• Design custom RL environments, verifiers and eval harnesses for agentic AI.
• Shape Lab platform roadmap from real customer field insights.

What they offer

• Cash compensation range $150-300k + equity incentives
• Flexible work (San Francisco or hybrid-remote)
• Visa sponsorship and relocation support
• Professional development budget
• Team off-sites and conference attendance

Ideal candidate

High-agency applied researcher who loves being embedded with customers, scoping ambiguous problems and shipping working agentic RL systems that advance open superintelligence.

Requirements

• Strong intuition for evaluation design: identify what to measure, how to construct rubrics, and where reward signal is weak
• Working understanding of RL and post-training concepts (GRPO, RLHF, reward modeling, SFT) and what the knobs do
• Strong Python skills and comfort with modern AI stack (Hugging Face, inference engines, agent frameworks)
• Experience in customer-facing or consulting-adjacent technical role, or as technical founder
• Excellent written and verbal communication for specs, case studies and customer support
• High agency and comfort with ambiguity - scope problems, ship solutions, and iterate