Senior AI Forward Deployed Engineer

Handshake

Senior Forward Deployed AI Engineer at Handshake, partnering with frontier AI labs for high-impact projects. Collaborating on AI training goals and creating evaluation frameworks.

Posted 7/2/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $250,000 - $290,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in applied Machine Learning and AI research engineering, with a strong focus on model training workflows, evaluation frameworks, and data quality. Proficient in Python and experienced in reinforcement learning concepts and ML data pipelines.

Highest-signal resume keywords

Applied Machine LearningPython ProgrammingReinforcement LearningML Data PipelinesModel Evaluation

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Hard Skills

Applied Machine LearningPython ProgrammingReinforcement LearningModel EvaluationExperiment TrackingData ProcessingLightweight OptimizationML Model Fine-TuningData Labeling SystemsQuality Metrics

Soft Skills

Excellent CommunicationStakeholder ManagementStrong Prioritization Instincts

Tools & Technologies

Annotation PipelinesBenchmark InfrastructureEval FrameworksPipeline Tooling

Industry Keywords

AI Research EngineeringPost-Training TechniquesModel Training WorkflowsFast-Moving Environments

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Partner directly with AI lab researchers to understand their post-training goals and data requirements
Design and deliver evaluation frameworks, annotation pipelines, and benchmark infrastructure tailored to each lab's training methodology
Prototype and iterate fast: stand up lightweight experiments, run evals, and interpret results
Make key design decisions around data quality and evaluation design
Mentor and uplevel other engineers and researchers on the team
Identify and document repeatable patterns across lab engagements
Stay current on the frontier: follow developments in RL, post-training, and benchmarking

Requirements

What you’ll need

6+ years of experience in applied ML, AI research engineering, or a closely related field with real exposure to model training workflows and post-training techniques
Strong Python skills and comfort working across the ML stack: data processing, model evaluation, experiment tracking, pipeline tooling
Solid working knowledge of reinforcement learning and post-training concepts (RLHF, DPO, PPO, etc.)
Hands-on experience fine-tuning or lightweight optimization of ML models (Tinker, LoRA, PEFT, or similar)
Experience with ML data pipelines and the tooling around them (e.g., data labeling systems, eval frameworks, quality metrics)
Excellent communication and stakeholder management
Strong prioritization instincts
Track record of leading technical projects end-to-end in ambiguous, fast-moving environments

Benefits

Comp & perks

Equity in a fast-growing company
401(k) match, competitive compensation, financial coaching
Paid parental leave, fertility benefits, parental coaching
Medical, dental, and vision, mental health support, $500 wellness stipend
$2,000 learning stipend, ongoing development
Commuting support, free lunch, and gym in our SF office
Flexible PTO, 15 holidays + 2 flex days
Team outings & referral bonuses