Founding Research Engineer – RL Environments & Evals

Rnb Consultancy; San Francisco (CA); Sur place; USD 150 000 - 200 000; Plein temps

Avantages offerts par ce poste

Base salary $150k–$200k

Equity 0.25–0.5%

Profit sharing up to 4% of project

Founding role with frontier labs

Résumé du poste

Rnb Consultancy in San Francisco invites an experienced AI software engineer to build RL environments and benchmarks for frontier models. As the first engineer in SF, you will design tasks, eval harnesses, and post-training experiments, and by month six lead a team.

The role demands full-time on-site work in SF with a 9-9-6 schedule. Base salary ranges from $150k to $200k plus equity (0.25–0.5%), and a potential 4% profit share that could push total pay toward $500k annually.

Qualifications

• Built RL environments, tasks, benchmarks or evaluation harnesses with your own hands.
• Hands-on post-training experience (SFT, DPO, GRPO, RLHF or similar) with tangible results.
• Able to work full time from the San Francisco office now, on a 9-9-6 schedule.
• Roughly 1–5 years of experience.

Responsabilités

• Design RL tasks and environments that frontier models train on.
• Develop eval harnesses and benchmarks to show model improvements.
• Conduct post-training experiments and translate findings into better environments.
• Hire and lead a team in San Francisco as the company grows.

Connaissances

RL environments

Post-training experience

Team leadership

Founding team mindset

Description du poste

Have you built the environments and benchmarks that AI models learn from? Then this is your seat.

A seed-stage AI company in San Francisco partners closely with the leading AI labs, creating the reinforcement learning tasks, environments and benchmarks those labs use to train and test their models. You'd be their first engineer in San Francisco, and from about month six you'd lead your own team.

What you'll own

• Designing and building RL tasks and environments that frontier models train on
• Eval harnesses and benchmarks that show whether a model actually got better
• Post-training experiments, and turning what you learn into better environments
• Hiring and leading a team in San Francisco as the company grows

Must-haves

• You've built RL environments, tasks, benchmarks or evaluation harnesses with your own hands. Only operating an existing eval pipeline won't be enough here.
• Hands-on post-training experience (SFT, DPO, GRPO, RLHF or similar), ideally with a result you can point to, such as a benchmark score that moved
• Able to work full time from the San Francisco office now, on a 9-9-6 schedule
• Roughly 1–5 years of experience

Bonus points

• A benchmark or post-training project of your own, public on GitHub
• Experience at a data or RL-environment company, or on a post-training team at an AI lab or strong university lab
• You're outside San Francisco but genuinely AI-obsessed and ready to move

What's in it for you

• $150k–$200k base, plus equity (0.25–0.5%)
• On top of that, 4% of project profits, which can realistically bring total pay to around $500k a year
• A founding role working side by side with frontier labs

Good to know

• Full-time, on-site in San Francisco, 9-9-6
• Sponsorship is limited: please tell us your exact work authorization up front
• Process: founder call - culture conversation with the co-founder - take-home build (RL and evals) - one day on site - offer