Staff/Principal Research Scientist
Snorkel AI · Redwood City, CA (Hybrid) | San Francisco, CA (Hybrid) | Remote (United States) · 316 - Research
About this role
Snorkel AI is hiring a staff-level Research Scientist in the machine learning function as a remote position. The posting calls out experience with Python, AWS, GCP, TensorFlow. Compensation is listed at $250,000–$350,000 per year.
- Role
- Research Scientist
- Function
- machine learning
- Level
- staff
- Track
- Tech leadership
- Employment
- Full-time
- Location
- Redwood City, CA (Hybrid) | San Francisco, CA (Hybrid) | Remote (United States)
- Work mode
- Remote
- Department
- 316 - Research
More roles at Snorkel AI
Job description
from Snorkel AI careersAbout Snorkel
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 between 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!
As a Research Scientist at Snorkel AI, you will bridge the gap between cutting-edge research and real-world AI systems. This is a hands-on role where you will prototype, build, and deploy innovative AI solutions—translating research breakthroughs into scalable, practical applications that solve real-world problems.
Snorkel AI operates in a fast-paced, high-impact environment, where we move quickly to push the boundaries of what’s possible. We’re looking for someone who thrives on rapid iteration, solving open-ended challenges, and driving innovation from research into production.