Senior Manager, Forward Deployed Research

Snorkel AINew York City, NY
Hybrid

About The Position

Snorkel AI is hiring a Senior Manager on the Forward Deployed Research team to own how we show what our data does. You own two related functions: benchmarking the latest frontier models against our data series to expose where they fall short, and tuning customer and open-source models on our data to demonstrate the lift it produces. Both become the evidence behind our data pitch and a signal for what to build next. This is a player-coach role. You own the system, the standards, and the output: the methodology, the quality bar, and the intelligence we produce, while hiring and developing a small team of engineers and researchers. You define the tooling and automation the function needs and partner with Engineering to build it. You stay hands-on in the technical work and grow the function as demand climbs. You partner across GTM, where this work opens and advances deals, with Research as a research partner, and with Engineering to build the underlying tooling. The right person is a strong engineer with real evaluation depth, can hold their own on frontier AI, and wants to own a function and grow a team.

Requirements

  • 8+ years in applied ML, model evaluation, or research-intensive engineering, with a track record of building technical systems
  • Strong software engineering skills, with experience building data or evaluation pipelines, automation, and tooling that scale
  • Deep understanding of model evaluation and benchmarking: designing evaluations, selecting model panels and metrics, and producing rigorous, defensible results
  • Strong fluency in frontier AI concepts including LLMs, evaluation methodologies, post-training techniques (RLHF, DPO, RLAIF), and domain areas such as coding agents, reasoning, multimodal models, or RL environments
  • Experience leading, hiring, and developing technical talent; comfortable as a player-coach who stays hands-on while growing a team
  • Ability to translate technical results into clear insights for technical and go-to-market audiences, and to partner effectively across research, engineering, and GTM
  • Ability to work in a fast-moving environment, comfortable with ambiguity and rapid iteration
  • M.S. in Computer Science, Machine Learning, or related field

Responsibilities

  • Own the system for measuring what our data does: define how we benchmark and tune models on our data, and the tooling and automation the function needs, partnering with Engineering to build it
  • Recruit, hire, and develop a small team of engineers and researchers; a player-coach role, hands-on technical work plus team leadership
  • Own the methodology and playbook for benchmarking and tuning: the model panels, the metrics we report, the tuning setups, and the quality bar, so results are consistent, repeatable, and defensible across accounts and data series
  • Turn benchmark results into gap intelligence: clear analyses of where models fall short that serve as the evidence behind our data pitch and a primary input to what we build next
  • Tune customer and open-source models on our data to demonstrate the lift it produces, and turn that into presales material and intelligence
  • Partner cross-functionally with the GTM team where this work opens and advances deals, with Research as a research partner, and with Engineering, who build the underlying platform and automation you direct
  • Serve as the technical authority on evaluation: escalation point for complex or high-stakes benchmarking, and the person ensuring our published pass rates and model comparisons are rigorous and credible

Benefits

  • Meaningful opportunities to shape priorities and initiatives
  • Influence key strategic decisions
  • Directly impact our ongoing success
  • Deepen your technical expertise
  • Explore leadership opportunities
  • Learn new skills across multiple functions
  • Supported in building your career in an environment designed for growth, learning, and shared success
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