Director, Applied Machine Learning

Job Description

Job Description

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.

• 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

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.

As Director of Applied ML, you'll lead the function that sits at the intersection of frontier AI research and enterprise-scale delivery. You'll own three core pillars: post-training and RL environments, scaled post-training infrastructure, and strategic project support across our lab partnerships. You think like an applied researcher, lead like an operator, and move fluidly between technical depth and client-facing strategy.

You'll build and grow a team, set the technical standards for how the team engages with frontier labs, and help shape the roadmap as we scale, not just execute against it. This is a rare opportunity to lead at the frontier of gen AI, with direct visibility into where model training is headed before the rest of the world sees it.

Location: San Francisco, CA | Hybrid, 3x a week in office

• Lead post-training and RL environment strategy — you don't need to be the deepest technical expert, but your team needs to be able to lean on you for real guidance grounded in lab experience

• Build and scale the infrastructure and team needed to run post-training at scale across multiple applied use cases

• Own strategic project support across lab engagements — leading your team through a dynamic, evolving roadmap rather than executing the work solo

• Manage and grow a team including AI Engineers, Research Scientists and AI Forward Deployed Engineers, with a path toward managing managers as the org scales

• Partner directly with AI lab researchers and internal stakeholders across engineering and operations, translating ambiguous priorities into clear direction for your team

• Maintain direct customer relationships, following up, communicating progress, and building trust with technical partners

• Bring organizational maturity to a fast-growing team: solve today's problems with today's resources while planning several steps ahead

• Stay current on the frontier: RL, post-training, and evaluation methods, bringing relevant insight into both team strategy and customer conversations

• Experience leading and growing technical teams, ideally with a research background in applied ML or AI

• Technical depth in applied AI systems design and model post-training (GRPO/PPO, SFT, or similar) enough to support a research-leaning team, though you don't need to have trained frontier models yourself

• Experience building and scaling teams or infrastructure in an applied, production environment

• Strong cross-functional leadership, comfortable working across engineering and operations, and managing shifting timelines with a team in tow

• Excellent client-facing communication skills — you can translate technical work into business impact and hold your own with both researchers and customers

• Organizational maturity and comfort with ambiguity — you'll need to be creative in solving problems as they arrive

• Prior lab experience depl