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Handshake

Senior Engineering Manager, Reinforcement Learning Environments

Handshake
🇺🇸San Francisco, CaliforniaHybrid$230K–$280K/yr1mo ago
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Summary

Lead a high-performing engineering team at Handshake building reinforcement learning environments where frontier AI models learn to complete end-to-end workflows across professional domains. Shape the technical direction of a critical platform at the intersection of platform engineering, applied AI infrastructure, and research tooling.

Key Responsibilities: Lead and mentor a team of 8-9 engineers, manage technical architecture for scalable environment systems, and collaborate with research, product, and operations teams to define roadmap and execution priorities. Drive engineering best practices around reliability, observability, and performance while balancing platform rigor with operational complexity.
Skills & Tools: Strong leadership and team development capabilities, technical expertise in platform and distributed systems, experience managing senior engineers and engineering managers. Familiarity with reinforcement learning or AI training infrastructure, with ability to drive cross-functional alignment in fast-paced environments.
Qualifications: Minimum 3 years of engineering management experience with increasing scope and ownership, including experience managing senior engineers and preferably an Engineering Manager. Technical background in platform systems, data pipelines, or AI training infrastructure.
Location: Hybrid in San Francisco, California, United States; 5 days/week in-office required
Compensation: $230,000 – $280,000 / annually

Job Description

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Fast Facts

Join Handshake as a Senior Engineering Manager to lead a team in building innovative reinforcement learning environments, significantly impacting AI model training across various professional domains.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Responsibilities: Lead and develop a high-performing team, manage technical architecture for scalable systems, and collaborate with cross-functional teams to define execution priorities.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Skills: Strong leadership in engineering management, technical expertise in platform and distributed systems, and experience in driving cross-functional alignment in fast-paced environments.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Qualifications: Minimum 3 years of engineering management experience, familiarity with reinforcement learning or AI training infrastructure, and a technical background in platform systems or data pipelines.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Location: San Francisco, California, United States; 5 days/week in-office required.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Compensation: $230000 - $280000 / Annually




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 expanding our team and seeking a Senior Engineering Manager to lead our Reinforcement Learning Environments (RLE) team.

The RLE team builds the sandbox environments where frontier AI models learn complete, end-to-end workflows. These environments simulate real-world professional domains such as software engineering, finance, and legal research — complete with realistic tools, constraints, and feedback loops. Instead of learning from static examples, models practice doing the work: navigating multi-step tasks, using domain-specific tools, handling ambiguity, and optimizing for real outcomes.

Researchers use these environments and the data they generate to train state-of-the-art models with reinforcement learning grounded in execution — not just prediction, but task completion, quality, and robustness in complex workflows.

As a Senior Engineering Manager, you’ll shape the technical direction and long-term strategy of this critical platform. You’ll lead a growing team (currently 9 engineers) and will likely manage an Engineering Manager in the near term. This is a highly strategic role sitting at the intersection of platform engineering, applied AI infrastructure, research tooling, and human-in-the-loop operations systems.

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

  • Lead and grow a high-performing team of 8–9 engineers building reinforcement learning environments
  • Manage, mentor, and develop senior engineers and future engineering leaders
  • Partner closely with research, product, and operations teams to define roadmap and execution priorities
  • Drive technical architecture for scalable, reliable, and extensible environment systems
  • Build plug-and-play environments that integrate seamlessly with model training pipelines
  • Balance platform rigor with operational complexity and data quality requirements
  • Establish engineering best practices around reliability, observability, and performance
  • Foster a culture of ownership, velocity, and high technical standards

Desired Capabilities

  • 3+ years of engineering management experience, with increasing scope and ownership
  • Experience managing senior engineers; experience managing an Engineering Manager (or equivalent scope) strongly preferred
  • 5+ years of prior hands-on engineering experience
  • Strong technical background in platform systems, distributed systems, or full-stack infrastructure
  • Experience building internal platforms, data pipelines, or research-facing tools
  • Proven ability to operate effectively in fast-paced, ambiguous environments
  • Experience driving cross-functional alignment across engineering, research, and operations
  • Willingness to work in-office in San Francisco 5 days/week

Extra Credit

  • Experience in reinforcement learning, simulation systems, or AI training infrastructure
  • Background in human-in-the-loop systems, data annotation platforms, or workflow tooling
  • Experience in operations-heavy, tech-enabled organizations
  • Familiarity with cloud infrastructure (AWS or GCP), APIs, and modern web stacks (e.g., React, TypeScript, Node.js, Python)
  • Experience building systems used by AI researchers or applied ML teams

What Success Looks Like

  • RLE becomes the default platform researchers use to train reinforcement learning workflows
  • New domains (e.g., finance, legal, SWE) can be launched quickly and reliably
  • Environment reliability and data quality are trusted by top AI research partners
  • The team scales with strong technical leaders who can independently drive new verticals
  • The RLE platform materially accelerates model capability in real-world task completion

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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