Senior ML & Research Engineer — Frontier AI Data Systems

Snorkel AI; New York (NY); Híbrido; USD 208.000 - 315.000; Jornada completa

Descripción de la vacante

Snorkel AI is building frontier AI data systems and scalable ML engineering tools. You will study how frontier-grade data is generated, form hypotheses, and validate them against real production data, shipping winners at scale.

Join an early ML & Research Engineering team shaping the discipline's direction and standards. Ideal candidates bring 5+ years of production ML experience, deep statistics knowledge, and strong Python/software skills to drive efficient evals, model routing, and

Formación

• 5+ years building production ML or software systems with end-to-end ownership.
• Hands-on experience running LLM/ML workloads in production and handling non-deterministic systems.
• Deep grounding in statistics: experiment design, hypothesis testing, sampling, confidence intervals.
• Strong Python and software engineering fundamentals: testing, code review, system design.
• Experience designing evaluations and interpreting results rigorously.
• Proactive problem finder with clear communication among researchers, engineers, and business partners.

Responsabilidades

• Efficiently manage end-to-end ML and research engineering tasks for frontier AI data.
• Study frontier-grade data generation, form hypotheses, and validate against production data.
• Ship scalable, reliable components used by researchers and engineers in production.
• Develop evaluation platforms and model routing to optimize cost and quality.
• Advance techniques for adaptive sampling, early stopping, and cost attribution.

Conocimientos

Production ML systems

End-to-end ownership

Python programming

Software engineering fundamentals

Experimentation and statistics

Non-deterministic ML reasoning

Educación

MS/PhD in CS/ML/Statistics

Descripción del empleo

Snorkel AI is building frontier AI data systems and scalable ML engineering tools. You will study how frontier-grade data is generated, form hypotheses, and validate them against real production data, shipping winners at scale.

Join an early ML & Research Engineering team shaping the discipline's direction and standards. Ideal candidates bring 5+ years of production ML experience, deep statistics knowledge, and strong Python/software skills to drive efficient evals, model routing, and