We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, 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!
We are looking for the founding members of our Operations engineering team. This team will be responsible for redefining how the world’s largest organizations meet large data annotation needs for groundbreaking models. Building on Snorkel AI’s core platform centered around programmatic data development, you will develop project-specific automations and optimizations to accelerate data generation, labeling, quality checks and more. These automation improvements will be used as critical product feedback to incorporate in our fast growing DaaS product. You will work closely with cross-functional teams such as research, engineering and operations to pioneer innovative workflows to power best-in-class ML models.
If you’re excited about defining the future of data-centric AI and delivering immediate business value to our customers by solving their data problem in a fast-paced environment, we’d love to have you on board! 🚀
Location: San Francisco (Hybrid)
Main Responsibilities- Prototype and build automation scripts for large-scale annotation workflows
- Be resourceful and creative in problem solving to meet customer requirements and deadline
- Create interactive dashboards in support of cross-functional partners in the operations and project management teams
- Design and optimize relational database schemas and complex queries to support high-performance data workflows.
- Work with OpenAI APIs and other LLM-related tools to develop AI/ML-powered features.
- Experience at a startup
- Familiarity with any scripting languages (python preferred) for data manipulation
- Experience with LLM prompting, LLM evaluation, and LLM related frameworks.
- Knowledge of non-relational databases (e.g., MongoDB, Redis).
- Experience with containerization using Docker and Kubernetes
The salary range for this position based in the San Francisco Bay Area is $200,000.00 - $250,000.00. All offers include equity compensation in the form of employee stock options.
Snorkel AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snorkel AI and has not been reviewed or approved by Snorkel AI.
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Healthcare Strength — Comprehensive medical, dental, and vision plans cover employees and dependents, with disability and life insurance included. A yearly wellness stipend supplements core health coverage.
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Leave & Time Off Breadth — Unlimited vacation, paid holidays, and paid sick days are offered. Company-wide rest days are also referenced, expanding time-off support.
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Parental & Family Support — Parental leave for birthing and non-birthing parents and childcare benefits are provided. Flexible work arrangements and remote-friendly perks further support family needs.
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What We Do
Our mission is to empower everyone to solve their most impactful problems through data-centric AI. To do this, we have introduced Snorkel Flow, a data-centric AI platform, and are building an incredibly talented team. We empower Fortune 500 enterprises such as Chubb and BNY Mellon, and several government agencies to accelerate AI application development by 10-100x.
Why Work With Us
The founding team spent over half a decade researching programmatic labeling, weak supervision, and other techniques to break through one of the biggest bottlenecks in AI: the lack of labeled training data. This research has resulted in Snorkel research project and 60+ peer-reviewed publications. Snorkel has developed and deployed its technology
