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Snorkel AI
Snorkel AI
51 – 200 Employees
H1B Visa SponsorConsultingHealthcareLogistics
Snorkel AI develops expert data solutions for machine learning teams. Its Expert Data-as-a-Service platform helps organizations create and evaluate high-quality training datasets, supporting faster model development and more reliable AI applications. Founded in 2019 from research at Stanford, the company works with organizations across consulting, healthcare, and logistics to advance practical AI systems.
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Senior AI and ML Software Engineer at Snorkel AI (Hybrid)

Senior/Staff machine learning engineer improving agent evaluation, model routing, and fine-tuned model systems. Build rigorous AI data infrastructure for Snorkel AI’s enterprise customers.

USUnited StatesCACalifornia
$208,000 – $315,000 / year
HybridFull-timeSeniorEnglish RequiredAI EngineerMachine Learning Engineer
Python

Description

  • Improve the speed, cost, and rigor of frontier AI data generation and evaluation through ML and AI
  • Investigate how frontier-grade data is produced and assessed
  • Develop hypotheses and test them against real production data
  • Scale approaches that demonstrate strong results
  • Reduce long-horizon agent evaluation costs through adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating
  • Direct evaluation and judge requests to the lowest-cost model that meets quality standards, with fallbacks, monitoring, and cost attribution
  • Fine-tune and deploy open-weight models with LoRA and other parameter-efficient techniques
  • Develop models that predict task difficulty for frontier systems before rollout
  • Create golden datasets and measure the accuracy and calibration of LLM-as-judge systems
  • Convert research prototypes into reusable, configurable components for production engineers and researchers
  • Help define ML engineering standards, guide discipline direction, and support the expanding team

Requirements

  • At least five years of experience building production machine learning or software systems, with ownership from prototype through production
  • Practical experience operating LLM or ML workloads in production
  • Ability to reason effectively about non-deterministic systems
  • Strong foundation in statistics and experimentation, including experimental design, hypothesis testing, sampling, and confidence intervals
  • Advanced Python and software engineering skills covering testing, code review, and system design
  • Experience creating evaluations and interpreting their results rigorously
  • Proactive identification of high-impact problems before they are formally assigned
  • Clear communication across research, engineering, and business teams

Benefits

  • Meaningful opportunities to influence priorities and initiatives
  • A voice in important strategic decisions
  • Direct contribution to Snorkel AI’s continued success
  • Opportunities to expand technical depth
  • Opportunities to lead
  • Chances to develop skills across multiple functions
  • Career development support within a growth-oriented environment focused on learning and shared success
  • Reasonable accommodations for applicants and employees with disabilities throughout application and interview processes, job performance, and access to employment benefits and privileges

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