Snorkel AI is looking to bridge the gap between cutting-edge research and real-world AI systems by prototyping, building, and deploying innovative AI solutions, translating research breakthroughs into scalable, practical applications that solve real-world problems.
Requirements
- Strong expertise in AI, NLP, multi-modal models, LLMs, and generative AI, with an emphasis on applied research and system-building.
- Experience in developing, experimenting, and deploying AI models at scale.
- Proficiency in Python and machine learning frameworks (NumPy, Scikit-learn, Pandas, PyTorch, TensorFlow, etc.).
- Experience with software engineering best practices (e.g., clean coding, modular design, version control).
- Familiarity with ML infrastructure, cloud platforms (AWS, Google Cloud), and accelerators (GPUs, TPUs).
Responsibilities
- Design, implement, and validate novel AI techniques for data development such as synthetic data generation, utilizing techniques such as LLM as a Judge
- Prototype and build end-to-end workflows, integrating research ideas into scalable systems.
- Write high-quality, maintainable code, ensuring robust implementation of research-driven innovations.
- Move fast and adapt—iterating on solutions in response to new challenges, customer needs, and emerging research.
- Work closely with real-world design partners, testing solutions in applied settings with measurable impact.
- Collaborate with research scientists, engineers, and industry partners to push forward Snorkel AI’s broader research initiatives and rapidly productionize prototypes.
Other
- Location: Redwood City or San Francisco OR REMOTE
- Ability to work in a fast-moving, iterative environment, comfortable with ambiguity and open-ended challenges.
- A bias for action—willing to roll up your sleeves, experiment, and move quickly to solve problems.
- This role is ideal for candidates who love both research and building real AI systems in a dynamic, high-impact setting.
- A Ph.D. in machine learning or a related field with a strong publication record is preferred, but we also welcome applications from those with equivalent expertise gained through industry experience, research labs, or other career paths.
