Director of Learning & Training — Remote, Equity, PTO

Handshake; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity ownership

401(k) match

Parental leave

Medical/dental/vision

Learning stipend

Office in SF

Flexible PTO

Team outings

Job summary

Handshake leads the Learning & Training function, shaping strategy and results for how fast fellows ramp and how high the quality of their work is.

This player-coach role blends leadership with hands-on course design and coaching across pods, setting the standard by example and by review.

You'll scale the model across more pods and project types, delivering training that improves data quality for labs and models.

Qualifications

• 8+ years in enablement, learning design, or training with team management.
• Willing to hustle as an IC and lead by example.
• Experience balancing multiple concurrent projects.
• Familiarity with AI models and data; coding not required.
• Ability to set and enforce quality standards.
• Proven ability to influence cross-functional partners.
• Comfort with ambiguity and fast-changing priorities.

Responsibilities

• Lead and develop the Learning & Training team.
• Stay hands-on by creating training and reviewing issues.
• Maintain a high quality bar across pods to ensure consistent design standards.
• Scale the forward-deployed model across pods and projects.
• Make ramp time and data quality improvements visible to leadership.
• Partner with operations to close training gaps.
• Drive strategic programs turning vision into shipped initiatives.

Skills

Leadership & Enablement

Player-coach mindset

Operations & capacity planning

AI model fluency

Data quality awareness

Influencing leadership

Adaptability & ambiguity

Job description

Handshake leads the Learning & Training function, shaping strategy and results for how fast fellows ramp and how high the quality of their work is.

This player-coach role blends leadership with hands-on course design and coaching across pods, setting the standard by example and by review.

You'll scale the model across more pods and project types, delivering training that improves data quality for labs and models.