Full-Stack Software Engineer, Reinforcement Learning
AI Summary
Builds full-stack tools and backend services for reinforcement learning data workflows, including dashboards, APIs, and partner-facing systems.
About this role
About the Role
Join an early-stage AI infrastructure team building the product interfaces, backend services, and internal tools that support reinforcement learning data workflows. You will work with research engineers and external partners to turn complex needs into polished products for creating, evaluating, and improving training data.
What You'll Do
Build tools for browsing environments, inspecting trajectories, reviewing task quality, and understanding model behavior.
Develop partner workflows for creating, submitting, testing, and iterating on environments and training data.
Create dashboards and observability tools for environment quality, evaluation results, data collection progress, and pipeline health.
Design backend services and APIs connecting task authoring, data collection, evaluation, quality review, and training systems.
Collaborate across research, operations, and go-to-market teams to ship useful systems amid evolving requirements.
What We're Looking For
At least 3 years of full-stack software engineering experience building and shipping production systems.
Proficiency in Python and a modern web stack such as React, TypeScript, or Next.js.
Experience owning user-facing or internal products from design through deployment.
Experience building data inspection, review, quality assessment, dashboard, or observability tools.
Experience with backend services, APIs, databases, cloud infrastructure, Docker, CI/CD, and production debugging.
Clear communication skills and the initiative to identify needs and improve products independently.
Experience with data collection, labeling, evaluation, developer tools, or partner-facing workflows is valuable. AWS, Kubernetes, Terraform, and Grafana experience is also useful.
Compensation & Benefits
Visa sponsorship and relocation support are available for strong full-time candidates relocating to the United States or Singapore.
Location
On-site in San Francisco, California. The team also has an office in Singapore.
Skills
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