The company is looking to bridge the gap between cutting-edge research and real-world AI systems by building innovative AI solutions 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
- A Ph.D. in machine learning or a related field with a strong publication record is preferred
- 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
