Applied Research Scientist
Snorkel AI
Redwood City, CA, USA
Posted on Wednesday, May 17, 2023
At Snorkel AI, we’re redefining how people and organizations build AI applications. Snorkel started as a research project in the Stanford AI Lab in 2016, creating a higher-level interface to machine learning through programmatically labeled and managed training data. From deploying in some of the world’s largest and most sophisticated tech organizations, to empowering scientists, doctors, and journalists — we’ve seen firsthand how this approach democratizes and accelerates AI. Now, we’re building Snorkel Flow to bring our technology to everyone!
Building Snorkel Flow requires outstanding engineers and technologies across the stack, including scalable data pipelines, elegant and intuitive interfaces (both visual and programmatic), state-of-the-art ML modeling techniques, and best practices for seamless deployment. Modern AI approaches require large labeled training datasets to learn from. While traditional approaches typically rely on armies of human annotators to label by hand, Snorkel Flow empowers users to programmatically label and build training data sets to drive a radically faster, more flexible, and higher quality end-to-end AI development process. Snorkel Flow is an end-to-end development platform, complete with a GUI and powerful programmatic interfaces for driving the development process for full AI application workflows: from preprocessing, to programmatic training data creation, to ML model training, to analysis, and deployment. It's the data-first platform for enterprise AI.
Excited to help us redefine how AI applications are built? Apply to be the newest Snorkeler!
Our goal at Snorkel is enabling next generation AI with data centric tooling to build, analyze and iterate on Machine Learning models. As an Applied Research Scientist, you will work on innovating and translating 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 run stable diffusion at scale for generating synthetic data?
- How to build a foundation model for a specific domain like medical records?
- How to build good multi-modal representations like CLIP but for spatial tasks like detection and segmentation?
- How to use models like LayoutLM V3 for weakly labeling documents at scale?
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.
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 integrate findings into Snorkel Flow
- 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)
Preferred Qualifications
- Broad expertise and understanding of Machine Learning and Systems
- 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.
Be Your Best At Snorkel
Snorkel AI is on a mission to make machine learning practical for everyone, and it starts with building a team that welcomes, represents and gives opportunity to all. We work at the frontier of AI and software engineering, and believe that underrepresented communities need to play a part in shaping the future of these fields. At Snorkel AI, we actively work to create an environment that values end-to-end ownership, diverse forms of impact, and opportunities for personal growth.
Snorkelers are supported by an amazing team and an amazing set of benefits. We offer comprehensive medical, dental, and vision plans for Snorkelers and their families, plus a yearly wellness stipend. Our 401k program lets Snorkelers plan for their future and our parental leave program lets new parents take up to 20 weeks of paid time off. Learn more about these benefits and more — like our workstation setup allowance — on our Careers page.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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