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Snorkel AI seeks an experienced engineer to develop and scale frontier AI data generation and evaluation methods, focusing on faster, cheaper, and more rigorous processes. The role involves engineering production ML workloads, model routing, and fine-tuning, turning research prototypes into reusable production components for engineers and researchers.
Candidates should have 5+ years in production ML, strong Python, and a solid statistics background, with proven ability to design evaluations and
Develop and scale methods that make frontier AI data generation and evaluation faster, less expensive, and more rigorous, including efficient agent evaluations, model routing, fine-tuned models, and predictive task difficulty. Establish measurement standards and turn research prototypes into reusable production components for engineers and researchers.
Requirements: Requires 5+ years building production ML or software systems, hands‑on experience with production LLM or ML workloads, strong Python and software engineering fundamentals, and rigorous grounding in statistics and experimentation. Candidates should have experience designing evaluations, interpreting results, and communicating effectively; fine‑tuning models, evaluation platforms, agentic workloads, and research‑to‑production experience are preferred.
Key Skills: Production Machine Learning, Python, Statistics, Experiment Design, Hypothesis Testing, Sampling, Confidence Intervals, LLM Evaluation, Model Routing, Fine‑Tuning, Open-Weight Models, Agentic Workloads, Software Engineering, System Design, Testing, Research-to-Production