Quick overview
Job description
About the Role
Join an early-stage AI company as its first engineering hire, building coding reinforcement learning environments and AI agents for enterprise use. You will work directly with the founders, shape technical direction, and help grow the engineering team.
What You'll Do
Build high-quality reinforcement learning environments and tasks using real-world enterprise data.
Build and deploy AI agents for enterprise customers.
Partner with company leadership on technical direction and the engineering roadmap.
Lead engineering as the team grows, shipping quickly while maintaining a high bar for quality.
What We're Looking For
At least 3 years of experience in reinforcement learning or AI agent development, or recent-graduate experience that includes 6 to 12 months building reinforcement learning environments or data.
Experience building coding reinforcement learning environments and shipping AI agents into production.
Strong reinforcement learning fundamentals, with experience training models using policy gradients, reward modeling, RLHF, or related methods.
Professional experience with Python and PyTorch or JAX, plus full-stack experience with TypeScript and AWS.
Daily use of AI-native development tools such as Claude Code, Cursor, or comparable tools.
Experience shipping products at startup pace. Distributed training, GPU infrastructure, mobile development, simulation frameworks, and reinforcement learning training libraries are useful additional experience.
A degree in computer science, mathematics, physics, or a related field is preferred. Experience with LLM post-training, agent training, open-source or research contributions, or early-stage AI teams is also valued.
Must be authorized to work in the United States without visa sponsorship and willing to relocate to San Francisco for an in-person 5.5-day work week.
Compensation & Benefits
Base salary: $125,000 to $200,000 annually. OTE (on-target earnings, base plus variable): $225,000 to $400,000. Visa sponsorship is not available.
Location
On-site in San Francisco, California. This role requires relocation to San Francisco and an in-person 5.5-day work week.
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