Senior AI Forward Deployed Engineer

Handshake Technologies, Inc.

Job Overview

Location

San Francisco, CA

Job Type

Full-time

Full Job Description

📋 Description

• Partner directly with frontier AI lab researchers to translate ambiguous post-training goals and data requirements into scoped, executable evaluation frameworks and annotation pipelines
• Design and deliver custom benchmark infrastructure tailored to each AI lab’s unique training methodology and model architecture
• Prototype and iterate rapidly on lightweight experiments, running evaluations and interpreting results in tight feedback loops with research partners
• Make critical design decisions around data quality, evaluation metrics, and pipeline scalability to ensure reliability at global scale
• Mentor and uplevel engineers and researchers on the team by establishing technical standards and best practices for forward-deployed AI work
• Identify and document repeatable patterns across customer engagements to accelerate future deployments and reduce duplication of effort
• Stay current on advancements in reinforcement learning, post-training techniques (RLHF, DPO, PPO), and benchmarking methodologies to inform customer conversations
• Own the full lifecycle of high-impact research engagements—from initial requirement gathering through deployment and iteration—with direct customer ownership
• Act as the primary technical liaison between Handshake AI and strategic partners, including leading frontier AI labs, Fortune 500 companies, and top educational institutions
• Translate researcher intuition into engineering reality by bridging gaps between academic research and production-grade tooling
• Drive prioritization across multiple urgent customer needs, guiding the team toward highest-leverage technical initiatives in fast-moving environments
• Build and maintain ML data pipelines using industry-standard tooling for data labeling, evaluation frameworks, and quality control systems
• Tinker with and fine-tune ML models using techniques such as LoRA, PEFT, or similar lightweight optimization methods in real-world settings
• Contribute to the evolution of Handshake AI’s internal systems by codifying learnings from customer engagements into reusable components and documentation
• Represent Handshake AI at the intersection of applied research and commercial delivery, ensuring technical credibility with researcher audiences
• Work hybrid in the San Francisco office three days per week, collaborating in person with engineers, scientists, and operators from top AI and tech organizations

🎯 Requirements

• 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, and 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 (e.g., LoRA, PEFT)
• Experience with ML data pipelines and tooling (e.g., data labeling systems, eval frameworks, quality metrics)
• Excellent communication and stakeholder management skills, with ability to translate between researcher intuition and engineering reality

🏖️ Benefits

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

Skills & Technologies

Python

Senior

Hybrid

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Handshake Technologies, Inc.

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About Handshake Technologies, Inc.

Handshake Technologies provides a cloud-based career-services platform that connects university students, recent graduates, and employers. The software enables institutions to manage job postings, career fairs, on-campus interviews, and employer relations while giving students tools to discover internships and entry-level roles and giving employers access to early-career talent across a network of partner colleges and universities.

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