Senior Engineering Manager, Reinforcement Learning Environments (RLE)
Role Overview
This is a senior leadership role managing a team of approximately 9 engineers building reinforcement learning environments that simulate real-world workflows. The manager will own the RLE roadmap, drive architecture for scalable environment systems, and build modular domains that integrate with training and evaluation loops. They will have direct impact on what AI models can learn, how quickly new domains launch, and the quality of research data.
Perks & Benefits
This is an in-office role in San Francisco requiring 5 days/week on-site with no remote or hybrid options. Benefits include equity, 401(k) match, comprehensive medical/dental/vision, mental health support, $500 wellness stipend, $2,000 learning stipend, paid parental leave, and fertility benefits. The company offers flexible PTO, 15 holidays plus 2 flex days, and team outings.
Full Job Description
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 Engineering Manager to lead our Reinforcement Learning Environments (RLE) team - the group building the interactive sandboxes where frontier models learn to complete real work.
RLE environments simulate end-to-end workflows across domains like software engineering, finance, and legal research, with realistic tools, constraints, and feedback loops. The platform generates high-signal interaction data researchers use to train and evaluate models for task completion, quality, and robustness.
This is a high-leverage role: the systems you lead directly shape what models can learn, how quickly new domains can launch, and how much researchers trust the signal. You’ll lead a team of ~9 engineers today and are expected to add leadership capacity (including managing an EM) as we scale.
Location: San Francisco, CA. This is an in-office role, 5 days/week (no remote/hybrid)
What You’ll Do
Lead, hire, and develop a high-performing team building RL environments and the platform behind them
Own the RLE roadmap and execution in close partnership with Research, Product, and Operations
Drive architecture for scalable, reliable, extensible environment systems and data generation pipelines
Build modular, plug-and-play domains that integrate cleanly with training and evaluation loops
Raise the bar on reliability, observability, performance, and data quality
Create a culture of ownership, speed, and strong engineering fundamentals in an ambiguity heavy setting
What We’re Looking For
Engineering leader + builder: 3+ years managing teams, plus 5+ years hands-on engineering experience
Strong people leadership: experience leading senior engineers; managing an EM (or equivalent scope) is a plus
Execution in ambiguity: proven ability to align cross-functionally and deliver in fast-moving, unclear problem spaces
Systems + product mindset: strong platform/distributed systems background, and the ability to turn research/ops needs into a clear roadmap, ship iteratively, and measure outcomes
Nice to Have
Experience with RL training infrastructure, simulation systems, or evaluation platforms
Human-in-the-loop systems (annotation, rubric tooling, QA pipelines, workflow platforms)
Operations-heavy, tech-enabled environment experience
Familiarity with AWS/GCP, APIs, Docker, and modern stacks (TypeScript/Node, React)
Experience building systems used by applied ML or AI research teams
What Success Looks Like
RLE becomes the default platform researchers use to train workflow-capable models
New domains launch quickly and reliably with trusted quality gates
Environment reliability + data quality are trusted inputs into training and evaluation decisions
The team scales with strong leaders who can independently drive new verticals
The platform measurably improves real-world task completion, robustness, and quality
Perks
Handshake delivers benefits that help you feel supported—and thrive at work and in life.
The below benefits are for full-time US employees.
🎯 Ownership: Equity in a fast-growing company
💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching
🍼 Family Support: Paid parental leave, fertility benefits, parental coaching
💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
📚 Growth: $2,000 learning stipend, ongoing development
💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office
🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days
🤝 Connection: Team outings & referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
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