Forward Deployed Research Engineer

### About the Role

We're a small, high\-caliber team building infrastructure for reinforcement learning environments and AI evaluation — helping frontier AI labs and data vendors train, evaluate, and align AI models to real\-world workflows. As a Forward Deployed Research Engineer, you'll own end\-to\-end resolution of urgent, ambiguous technical challenges for our most important customers and partners. You'll be the person who unblocks critical deployments, turns repeated firefighting into reusable tooling, and operates with speed and sound judgment in fast\-moving situations.

This is a hands\-on, high\-impact role at the intersection of applied AI engineering and customer\-facing problem solving. You'll work directly with frontier AI labs, post\-training data vendors, and internal research and go\-to\-market teams.

### What You'll Do

• Take the lead on diagnosing and resolving ambiguous technical problems across code, data, and environments.
• Own technical deployment requests from AI labs, data vendors, and internal teams — from triage through to completion.
• Ask the right questions to clarify underspecified asks and identify what actually needs to be done.
• Build tools and one\-off pipelines to solve urgent customer or partner problems quickly.
• Coordinate with research and GTM teams to unblock deployments and move work forward.
• Balance speed and quality in situations where customers need fast turnaround and the path isn't fully specified.
• Document recurring issues and convert repeated manual work into reusable tools and processes.

### What We're Looking For

Required:

• 2–4 years of experience in applied research engineering, forward\-deployed engineering, or similar hands\-on technical roles.
• Strong generalist AI engineering skills with a bias for moving quickly and iterating.
• Proficiency in Python, Docker, and Linux environments.
• Experience working on benchmarks and evals, with sound judgment about what makes a task realistic, a rubric reliable, and a trajectory useful for RL training.
• Strong debugging instincts across code, data, and complex environments.
• Demonstrated ability to operate independently in ambiguous situations without a fully prescribed roadmap.
• Clear judgment about when to move fast, when to escalate, and when correctness or security requires extra care.
• Comfort working directly with technical customers, vendors, or cross\-functional internal teams.
• Experience handling urgent production, customer, or deployment issues under pressure.
• Early\-stage startup experience and a proven ability to work independently in fast\-paced environments.
• Strong written and verbal communication skills for remote collaboration across time zones.

Nice to Have:

• Prior experience at a customer\-facing or forward\-deployed engineering role at an AI/ML company.
• Familiarity with RL training pipelines, reward modeling, or post\-training data workflows.
• A desire to work closely with frontier AI labs and data vendors on cutting\-edge alignment challenges.

### Compensation \& Benefits

• Salary: $150,000 – $250,000 USD annually, depending on experience.
• Equity participation in an early\-stage, venture\-backed AI infrastructure company.
• Visa sponsorship is available.

### Location

This role is based on\-site in San Francisco, CA. We're looking for candidates who are able to work in\-person with the team. Candidates based in or willing to relocate to San Francisco are strongly preferred.