Software Engineer — Backend

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!

You will be part of the backend team that is building a scalable and reliable distributed system that empowers users to solve their most pressing needs in a data-centric AI world. The team has a variety of technical backgrounds, from machine learning PhDs to full-stack engineers who are building large-scale production systems. You will become one of these pragmatic, high-output, product-focused engineers.

• Own the architecture, design, development, and operations of large-scale systems designed for AI/ML tasks including distributed compute systems, data management systems, data engineering workflow systems, and end user experiences
• Prototype, optimize, and maintain scalable back‑end services that will power new ML and foundation model powered development workflows
• Design extensible and testable interfaces between internal services including the underlying storage and data models
• Keep CI/CD pipelines healthy and support customers in production via engaged on‑call support
• Be an engaged team player in a customer‑focused cross‑functional environment where you will feel excited to take on whatever is most impactful for the company and product
• Work a hybrid schedule with one or two days per week in our Redwood City HQ and work remotely with No Meeting Tuesdays and Thursdays

• Bachelor's degree in Computer Science or related field
• 2 years experience in delivering distributed and ML systems and services in a production setting for cloud-native applications
• Experience with distributed compute frameworks and data processing pipelines
• Ability to design and build efficient scalable data storage, compute, and retrieval systems for AI/ML tasks
• Strong communication and coding skills with emphasis on designing for scale and robustness
• Strong development and debugging skills in python

• 5 years of professional software engineering experience
• Experience with architecting and developing production web‑scale systems (monitoring, telemetry, performance, reliability, triage and debug)
• Experience working with ML systems and foundation models (e.g. large language models)
• Experience owning delivery of large multi-person multi-quarter projects
• Experience developing enterprise software products for machine learning and/or data science applications

The salary range for this position based in the San Francisco Bay Area is $ - $. All offers include equity compensation in the form of employee stock options.

Be Your Best At Snorkel

Snorkel AI is on a mission to make machine learning practical for everyone, and it starts with building a team that welcomes, represents and gives opportunity to all. We work at the frontier of AI and software engineering, and believe that underrepresented communities need to play a part in shaping the future of these fields. At Snorkel AI, we actively work to create an environment that values end‑to‑end ownership, diverse forms of impact, and opportunities for personal growth.

Snorkelers are supported by an amazing team and an amazing set of benefits. We offer comprehensive medical, dental, and vision plans for Snorkelers and their families, plus a yearly wellness stipend. Our 401k program lets Snorkelers plan for their future and our parental leave program lets new parents take up to 20 weeks of paid time off. Learn more about these benefits and more — like our workstation setup allowance — on our Careers page.