Handshake
Associate Software Engineer, RLE
About this role
Join Handshake AI's RLE platform team as an Associate Software Engineer to build reinforcement learning environments where frontier AI models train on real-world tasks. You'll contribute across backend systems and frontend interfaces while learning from senior engineers in a fast-paced, in-office environment in San Francisco.
What you'll do
- Build and enhance Reinforcement Learning Environment (RLE) systems and supporting infrastructure
- Implement backend and frontend features across the platform
- Collaborate with senior engineers to improve system reliability and performance
- Develop modular workflow domains spanning engineering, finance, legal, and other domains
- Support data pipelines that enable model training and evaluation
What they're looking for
- Backend development and API design
- ReactJS and TypeScript
- PostgreSQL and database fundamentals
- System design principles
- Fast-paced learning and execution
- Cloud platforms (AWS or GCP preferred)
- Data pipeline experience
- ML/AI or simulation systems knowledge
Benefits
- Equity ownership in a rapidly growing company
- Competitive compensation with 401(k) match
- Comprehensive medical, dental, and vision coverage
- $2,000 annual learning stipend and ongoing development
- Flexible PTO, 15 holidays plus 2 flex days
- Free lunch, gym access, and commuting support at SF office
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Handshake
Handshake is a platform that connects students and job seekers with employers through job discovery and matching. The company is hiring iOS engineers, machine learning engineers, AI software engineers, and AI domain experts to build personalization systems, mobile experiences, and production AI solutions for both consumer and enterprise customers.
- Website
- handshake.com
Likely interview questions
- Walk us through a backend API or feature you've built—how did you structure it and what challenges did you encounter?
- Tell us about your experience working with React and TypeScript. What patterns or mistakes have you learned from?