Director, Applied Machine Learning

About the role

Handshake AI operates at the intersection of frontier research and large-scale data infrastructure. This leadership role oversees the development of post-training environments and the technical strategy for our partnerships with major AI labs.

Key facts

What you'll do

• Direct the strategy for reinforcement learning environments and post-training workflows.
• Scale the infrastructure and engineering team required to support diverse applied AI use cases.
• Manage a team of AI engineers, research scientists, and forward deployed engineers, with a focus on future management-level growth.
• Serve as the primary technical lead for lab partnerships, translating research objectives into actionable project roadmaps.
• Maintain direct communication with technical stakeholders to build trust and ensure project alignment.
• Balance immediate operational demands with long-term organizational planning.
• Monitor developments in evaluation methods, RL, and post-training to inform team strategy.

Requirements

• Experience managing and expanding technical teams, preferably within an applied AI or research environment.
• Technical understanding of model post-training, such as SFT, PPO, or GRPO, sufficient to guide a research-focused team.
• Proven ability to build and scale infrastructure in production-heavy settings.
• Strong cross-functional leadership skills with the ability to manage shifting priorities between engineering and operations.
• Professional communication skills capable of bridging the gap between technical research and business outcomes.
• Ability to navigate ambiguity and implement organizational structure in a high-growth environment.

Nice to have

• Background in deploying or training agents for real-world applications within a lab setting.
• Experience managing other managers or scaling departments through multiple growth phases.
• Knowledge of large-scale human feedback collection, annotation tools, or evaluation frameworks.

Skills & tools

• Applied ML
• Post-training (SFT, PPO, GRPO)
• AI systems design
• RL environments
• Infrastructure scaling
• Technical team leadership

Practical notes

• Benefits include 401(k) matching, medical, dental, and vision coverage, and mental health support.
• Financial perks include a $500 wellness stipend and financial coaching.
• Professional development includes a $2,000 learning stipend.
• Family support includes paid parental leave, fertility benefits, and parental coaching.
• Office amenities in San Francisco include commuting support, daily lunch, and a gym.
• Time off includes flexible PTO, 15 holidays, and 2 flex days.