Senior AI Forward Deployed Engineer

Apply; San Francisco (CA); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Equity in a fast-growing company

401(k) match

Paid parental leave

$500 wellness stipend

$2,000 learning stipend

Job summary

Apply is seeking a Senior Forward Deployed AI Engineer to work in San Francisco, CA. In this hybrid role, you'll bridge applied AI research and customer delivery, collaborating with leading AI labs.

The ideal candidate has extensive experience in ML and AI engineering, a strong background in Python, and familiarity with reinforcement learning. You'll play a critical role in prototyping and executing high-impact research projects.

Qualifications

• 6+ years of experience in applied ML, AI research engineering, or a closely related field.
• Hands-on experience fine-tuning ML models.
• Experience with ML data pipelines and related tooling.

Responsibilities

• Partner with AI lab researchers to understand their goals and data requirements.
• Design evaluation frameworks and benchmark infrastructure.
• Mentor engineers and researchers on technical standards.

Skills

Python skills

Applied ML experience

Stakeholder management

Technical project leadership

Experience with ML data pipelines

Reinforcement learning knowledge

Education

6+ years in AI research engineering or related field

Tools

Data processing tools

Model evaluation frameworks

Job description

About the Role

As a Senior Forward Deployed AI Engineer, you'll sit at the intersection of applied AI research and customer delivery embedded with our most strategic partners, including leading frontier AI labs. You think like a researcher and ship like an engineer. You speak the language of the labs. You default to action and figure things out in motion.

You'll own the full lifecycle of high-impact research engagements from translating ambiguous lab requirements into concrete evaluation frameworks to prototyping pipelines and tooling that make them run. You'll make fast decisions, lead prioritization decisions, mentor engineers, and establish the patterns and systems that others follow. Your technical credibility with researcher audiences and your ability to move quickly in shifting environments are what set you apart.

This is a rare role: deep AI knowledge, real customer ownership, and the chance to influence how frontier models get trained.

Location

San Francisco, CA | Hybrid, 3x a week in office.

What you'll do

• Partner directly with AI lab researchers to understand their post-training goals and data requirements, translating ambiguous research questions into scoped, executable projects.

• 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 in tight feedback loops with research partners.

• Make key design decisions around data quality and evaluation design that hold up at scale.

• Mentor and uplevel other engineers and researchers on the team, establishing technical standards for forward-deployed AI work.

• Identify and document repeatable patterns across lab engagements to accelerate future deployments.

• Stay current on the frontier: follow developments in RL, post-training, and benchmarking to bring relevant insight into every customer conversation.

What we're looking for

• 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.). You don't need to have trained frontier models, but you need to hold your own in a room of people who have.

• Hands-on experience fine-tuning or lightweight optimization of ML models (Tinker, LoRA, PEFT, or similar). You've actually tinkered with models, not just read about it.

• Experience with ML data pipelines and the tooling around them (e.g., data labeling systems, eval frameworks, quality metrics).

• Excellent communication and stakeholder management. You’re an apt translator between researcher intuition and engineering reality, and build trust with both.

• Strong prioritization instincts: you know how to triage across multiple urgent customer needs and guide your team toward the highest-leverage work.

• Track record of leading technical projects end-to-end in ambiguous, fast-moving environments.

Extra Credit

• Experience with evaluation design for LLMs or RLHF pipelines in production customer environments.

• Published research or benchmarking work, or contributions to open-source AI/ML tooling.

• Prior experience in a forward-deployed, solutions engineering, or technical consulting role at a high-growth AI company.

• Familiarity with annotation platform tooling, quality control frameworks, or human feedback collection at scale.

Perks

Handshake delivers benefits that help you feel supported—and thrive at work and in life.

The below benefits are for full-time US employees.

Ownership: Equity in a fast-growing company

Financial Wellness: 401(k) match, competitive compensation, financial coaching

Family Support: Paid parental leave, fertility benefits, parental coaching

Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend

Growth: $2,000 learning stipend, ongoing development

Office: Commuting support, free lunch, and gym in our SF office

Time Off: Flexible PTO, 15 holidays + 2 flex days

Connection: Team outings & referral bonuses