Senior Software Engineer (RLE)

🇺🇸 San Francisco, California
$2K - $3K Annual
Posted 2 weeks ago
Expires June 28, 2026

ABOUT HANDSHAKE

Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.

Why join Handshake now:

- Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel

- Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions

- Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others

- Build a massive, fast-growing business with billions in revenue

ABOUT THE ROLE

We’re hiring a Senior Software Engineer to build our Reinforcement Learning Environments (RLE) platform—the interactive systems where frontier AI models learn to complete real-world work.

RLE environments simulate workflows (e.g., software engineering, finance, legal) with realistic tools, constraints, and feedback loops. The data generated powers training and evaluation for model quality, robustness, and task completion.

This is a high-ownership role with direct impact on how models learn and how quickly new domains scale.

Location: San Francisco, CA (in-office, 5 days/week)

WHAT YOU’LL DO

- Build and scale our reinforcement learning environments and the platforms behind them

- Drive architecture for scalable, reliable, extensible environment systems and data generation pipelines

- Partner with Research, Product, and Ops to turn ambiguous needs into production systems

- Build modular, plug-and-play domains that integrate cleanly with training and evaluation loops

- Raise the bar on reliability, observability, performance, and data quality

WHAT...

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