Senior AI Forward Deployed Engineer

About the role

Join Handshake AI to shape the future of careers in the AI economy. This role involves direct collaboration with leading AI labs, translating their research needs into practical engineering solutions. You will drive the development of evaluation frameworks and data pipelines, influencing how frontier models are trained at a global scale.

Key facts

What you'll do

• Work directly with AI lab researchers to define and scope ambiguous research goals into actionable projects.
• Create and implement evaluation frameworks, data annotation pipelines, and benchmark infrastructure for specific lab training methods.
• Rapidly prototype experiments, conduct evaluations, and interpret results in close collaboration with research partners.
• Make critical decisions regarding data quality and evaluation design that scale effectively.
• Mentor and elevate other engineers and researchers, setting technical standards for forward-deployed AI initiatives.
• Identify and document recurring patterns across lab engagements to accelerate future deployments.
• Stay informed about advancements in reinforcement learning, post-training, and benchmarking to provide relevant insights to customers.

Requirements

• 6+ years of experience in applied ML, AI research engineering, or a similar field with exposure to model training and post-training techniques.
• Strong Python proficiency and comfort across the ML stack, including data processing, model evaluation, experiment tracking, and pipeline tools.
• Solid understanding of reinforcement learning and post-training concepts (e.g., RLHF, DPO, PPO).
• Practical experience fine-tuning or optimizing ML models using methods like Tinker, LoRA, or PEFT.
• Experience with ML data pipelines and associated tooling, such as data labeling systems and evaluation frameworks.
• Excellent communication and stakeholder management skills, capable of bridging researcher intuition with engineering realities.
• Strong prioritization abilities to manage multiple urgent customer needs and guide the team towards high-impact work.
• Proven track record of leading technical projects from start to finish in dynamic and ambiguous environments.

Nice to have

• Experience designing evaluations for large language models or RLHF pipelines in production environments.
• Published research, benchmarking work, or contributions to open-source AI/ML tools.
• Previous experience in a forward-deployed, solutions engineering, or technical consulting role at an AI growth company.
• Familiarity with annotation platform tooling, quality control frameworks, or large-scale human feedback collection.

Skills & tools

• Python
• ML stack (data processing, model evaluation, experiment tracking, pipeline tooling)
• Reinforcement Learning (RLHF, DPO, PPO)
• ML model optimization (Tinker, LoRA, PEFT)
• ML data pipelines
• Data labeling systems
• Evaluation frameworks

Practical notes

This role offers equity in a rapidly growing company. Benefits include a 401(k) match, paid parental leave, fertility benefits, medical/dental/vision coverage, mental health support, a $500 wellness stipend, a $2,000 learning stipend, flexible PTO, 15 holidays plus 2 flex days, commuting support, free lunch, and a gym in the SF office.