СШАSenior | Staff Software Engineer - AI / ML
2 нед. назад
208k–315k USD / годСШАLeadHybrid
machine learningdata analysispythonml
Senior Staff Software Engineer role working on AI/ML data engineering and research to optimize frontier AI data generation and evaluation.
О компании
- At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.
- We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
- In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand.
Обязанности
- Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI
- You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it.
Требования
- 5+ years building production ML or software systems, with end-to-end ownership from prototype to production
- Hands-on experience running LLM or ML workloads in production, and comfort reasoning about non-deterministic systems
- Deep grounding in statistics and experimentation: experiment design, hypothesis testing, sampling, and confidence intervals
- Strong Python and software engineering fundamentals, including testing, code review, and system design
- Experience designing evaluations and interpreting results rigorously
- A habit of finding high-impact problems before they are assigned, and clear communication with researchers, engineers, and business partners
Будет плюсом
- Fine-tuning and serving open-weight models, and judging when a smaller model meets the quality bar
- Building LLM evaluation or experimentation platforms, model gateways, or routing systems
- Experience with agentic workloads, benchmarks, or RL environments
- A record of taking research into production: publications, open-source work, or shipped research-driven features
- MS or PhD in Computer Science, Machine Learning, Statistics, or a related field
Условия
- Frontier problems. Measure and shape the tasks designed to challenge the strongest models in the world.
- All AI, no plumbing. Every problem on this team is an open ML or LLM problem.
- Founding impact. Help define what ML engineering means at Snorkel and grow the team that carries it forward.
- Visible results. Your work shows up directly in the speed, quality, and cost of the data frontier AI is built on.
- Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.
- Salary range(s) for this role
- $208,000 — $315,000 USD
Другое
- Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating.
- AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution.
- Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other parameter-efficient methods) where they match frontier quality, and know when they don't.
- Predictive difficulty. Build models that estimate how hard a task is for frontier systems before running a single rollout.
- Measurement for AI data. Build golden datasets, quantify the accuracy and calibration of LLM-as-judge systems, and make quality reproducible across projects.
- Research to production. Turn research prototypes into reusable, configurable components that forward deployed engineers and researchers use on every project.
- Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.