Staff Applied Research Scientist

As an Applied Research Scientist, you will innovate and translate cutting edge research into user experiences. If you find yourself thinking about any of these questions:

• How to prompt a model like GPT-4 effectively?
• How to build a foundation model for a specific domain like medical records?
• How to use models like LayoutLM V3 for weakly labeling documents at scale?
• How to blend prompt engineering, retrieval augmentation, and fine-tuning to customize models with the least human time and effort?

We would love to hear from you! More broadly you will work on supervision (self-supervised, semi-supervised, weakly supervised etc) and representation learning methods which result in practical tooling for building and maintaining state-of-the-art machine learning models at scale.  

• Establish and empirically demonstrate the state-of-the-art approaches for data-centric model iteration and analysis 
• Prototype end-to-end workflows with novel techniques and algorithms, synthesize results, and help to transfer learnings into Snorkel products
• Work closely with design partners to validate your work on real-world use cases with measurable impact
• Contribute to novel research on topics of interest to Snorkel AI by collaborating with other Snorkel Research scientists and affiliate scientists (academic, government, and industry researchers)
• 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

• Broad expertise and understanding of AI, NLP, LLM, and generative AI trends.
• Experience prototyping, experimenting, and testing with large scale datasets and training deep models.
• Experience with standard machine learning frameworks and tools (NumPy, Scikit-learn, Pandas, Pytorch, TensorFlow, etc.) and machine learning cloud infrastructure and accelerators (AWS, Google Cloud, GPUs and TPUs).
• Strong technical communication skills and the ability to work in a fast-paced environment.
• Experience with developing robust software with excellent coding hygiene and modular design.
• The position involves working with problems with no off-the-shelf solutions and requires innovation on-the-fly. Typically a Ph.D. in machine learning or a related area with good publication history would be a good fit for this position. We would also love to hear from people with similar skill sets acquired through other career paths.