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!

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’re looking for a talented researcher to join the team to work on foundational multimodal problems with the focus on data development techniques.  

Main Responsibilities

• 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 in our Redwood City HQ and work remotely with "No Meeting" Tuesdays and Thursdays

Preferred Qualifications

• PhD + 2+ YOE working on applied research on Computer Vision tasks
• Experience with 3D Computer vision 
• Experience handling large scale medical imaging datasets including CT-Scan or robotics LiDAR datasets.
• Experience in delivering one or more of these domains: Large vision language models, visual question answering, image-text alignment, text to image, text to video, text to motion, image to video, image captioning, activity/action recognition, Augmented and Virtual reality, object detection, semantic segmentation, depth estimation, trajectory prediction, pose estimation, keypoint detection and tracking, medical vision (MRI, CT-Scan, X-ray), perception (robotics/autonomous agents).
• 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.