Director, Learning and Training

Handshake•San Francisco, CA

4d•$200,000 - $260,000

About The Position

Handshake AI’s Learning & Training (L&T) function prepares Fellows to work on AI projects and develops them into high-quality AI training talent. The team teaches Fellows how models work, how to identify hallucinations, how to provide structured feedback that improves models, and how to reason about alignment and safety. L&T uses a forward-deployed model: learning designers embed in project pods with operations and turn new lab specifications into training quickly, including playbooks, courses, interactive tools, and targeted coaching. Approximately 80% of the team’s time is spent in pods and 20% on shared systems such as assessment, analytics, and rubrics. The Director will lead L&T as it joins Central Ops, reporting to the VP of Central Ops. This player-coach owns the function’s strategy, team, and results, including Fellow training speed, ramp-up, and work quality. The role leads four senior learning designers while also contributing hands-on when needed by building training, reviewing Fellow errors, and setting standards through example and review. The Director will lead the existing team and model, scale it across more pods and project types, and make the function’s impact clear to operations and leadership. The role works closely with fellow experience, quality, and delivery, and shapes training that informs the data used by frontier AI labs to improve models.

Requirements

At least 8 years of experience in enablement, learning design, or training.
At least 3 years managing a team of experienced individual contributors.
A player-coach mindset and willingness to contribute as an individual contributor when needed.
Experience managing capacity across many concurrent projects where training is delivered in days rather than quarters.
Fluency with AI models and data, including daily use of models, understanding how they fail, and understanding how data quality shapes model behavior; coding is not required.
A track record of defining and maintaining quality standards through standards, review, and coaching.
Ability to influence operations leaders and communicate the case for a function using measurable outcomes.
Comfort with ambiguity and with a function that is still taking shape.

Nice To Haves

Background in human data, data annotation, RLHF, or model evaluation.
Experience training domain experts such as PhDs, engineers, or professionals rather than general audiences.
Familiarity with technical or coding training, or AI safety evaluation.
Experience building learning analytics or skills assessment systems.
Hands-on comfort with SQL, scripting, or evaluation tooling.

Responsibilities

Lead and develop the team, coach senior individual contributors, and grow future leads from within.
Stay hands-on by joining pods when demand spikes or projects are new, building training, reviewing Fellow errors, and modeling expected standards.
Maintain a written design standard across pods to ensure consistent quality.
Scale the forward-deployed model by planning capacity, prioritizing projects and system work, and deciding where to embed, consult, or enable pods to self-serve.
Make the impact of training visible by communicating ramp time, Fellow quality, and project outcomes to operations and leadership.
Partner with fellow experience, quality, and delivery to identify training gaps before they become quality issues.
Turn the function’s vision into strategic programs that ship and are adopted.
Hire and grow the team as demand increases, including expertise in technical and safety areas.