Full-Stack Software Engineer, Reinforcement Learning
$100k - $225k • Remote • San Francisco • FullTime
Posted 1mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
RAG Engineer
About the job
HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI trainers. We are a rapidly growing team of researchers, engineers, and operators backed by significant VC funding. This role focuses on building the product surfaces, backend systems, and internal tools that power HUD's Reinforcement Learning (RL) data engine. You will own product surfaces end-to-end, translating ambiguous needs into polished products that enable our RL systems by working closely with research engineers and vendors.
Responsibilities
- Develop product-facing tools for browsing environments, inspecting trajectories, reviewing task quality, debugging failures, and understanding model behavior.
- Build vendor-facing workflows for external partners to create, submit, test, and iterate on RL environments and training data.
- Create dashboards and observability tools for environment quality, evaluation results, data collection progress, grader issues, reward signal problems, and pipeline health.
- Design backend services and APIs connecting task authoring, data collection, evaluation, QA/QC, and RL training infrastructure.
- Partner with research, operations, and GTM teams to translate requests into well-designed systems.
Requirements
- Strong software engineering fundamentals and full-stack range.
- Proficiency in Python and a modern web stack (e.g., React, TypeScript, Next.js).
- Experience owning user-facing or internal products end-to-end.
- Good product taste and ability to build intuitive tools for technical and non-technical users.
- Comfort with cloud infrastructure, Docker, CI/CD, observability, and production debugging.
- High agency: identify needs, build solutions, and improve them independently.
- Strong communication skills for cross-functional collaboration.
- Experience building data collection, labeling, annotation, eval, or research tooling platforms (preferred).
- Experience building dashboards, review workflows, observability tools, or debugging interfaces for complex systems (preferred).
- Experience building developer tools, infrastructure products, internal platforms, or workflow products (preferred).
- Experience with AWS, Kubernetes, Terraform, Docker, Grafana, or similar infrastructure tools (preferred).
Benefits
- Competitive compensation
- 100% covered top-of-the-line medical, dental, and vision (US and Singapore)
- Lunch and dinner for in-office employees
- Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays
- Equinox membership (US)
- 401k (US)
- Commuter benefits (US)
- Health/wellness stipend (Singapore)
- Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
- Annual travel budget to visit either office