Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.
In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.
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
Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders
Build a massive, fast-growing business with billions in revenue
About Handshake AI
Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.
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 ~7 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 DoLead, 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
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
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
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
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.
Skills Required
- 3+ years of engineering management experience
- Experience managing senior engineers
- Experience managing an Engineering Manager (or equivalent scope)
- 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
- Experience in reinforcement learning, simulation systems, or AI training infrastructure
- Background in human-in-the-loop systems, data annotation platforms, or workflow tooling
- Familiarity with cloud infrastructure (AWS or GCP), APIs, and modern web stacks (React, TypeScript, Node.js, Python)
- Experience building systems used by AI researchers or applied ML teams
Handshake Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Handshake and has not been reviewed or approved by Handshake.
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Leave & Time Off Breadth — Time-off practices include flexible/unlimited PTO, companywide recharge weeks in summer and winter, plus additional volunteer and personal holiday time. Feedback suggests sabbaticals and coordinated breaks help people actually use rest time.
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Parental & Family Support — Parental leave is described as extended for primary and secondary caregivers, and family-oriented policies are highlighted. Fertility and family-support resources are referenced in public materials.
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Healthcare Strength — Core coverage spans medical, dental, and vision, with added mental-health resources and wellness programming. Feedback suggests these supports contribute meaningfully to overall wellbeing.
Handshake Insights
What We Do
Handshake is the #1 place to launch a career with no connections, experience, or luck required. The platform connects up-and-coming talent with 650,000+ employers - from Fortune 500 companies like Google, Nike, and Target to thousands of public school districts, healthcare systems, and nonprofits. Earlier this year, we announced our $200M Series F funding round. This Series F fundraise and new valuation of $3.5B will fuel Handshake’s next phase of growth and propel our mission to help more people start, restart, and jumpstart their careers.
Why Work With Us
How someone builds their career is foundational. We believe in working with the higher education community to help students build meaningful careers. We are at the nexus of universities, students and employers— and we’re able to connect the very best pieces of each side. We’re proud to create a community where students can be more successful.
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