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 Machine Learning Engineer, you’ll research and utilize established and state-of-the-art machine learning (ML) techniques to successfully deliver solutions to our customers. You'll engage new ML use cases through hands-on customer problems and help generalize learnings into the core Snorkel Flow platform. We move fast and are constantly prototyping new ways to deliver value to our customers. The road from A to B isn’t always clear-cut, and the impact of our work is global. Our team is mission-driven and customer-obsessed, and we are looking for an intellectually curious and energetic individual who can replicate this model across our ML initiatives.

Main Responsibilities

• Assist customers with the delivery of a Machine Learning project from beginning to end, including business case definition and scoping, data aggregation and exploration, algorithm selection, and model deployment to deliver business impact to the organization
• Present findings and recommendations to customer stakeholders, assist with program ideation and technical program management, and brief materials.
• Design, develop, and deploy enterprise AI/ML solutions across various industries like finance, healthcare, insurance, retail and more
• Serve as the voice of our customers for new ML paradigms, data science workflows, and share customer feedback to product teams

Preferred Qualifications

• 5+ years of professional experience with machine learning, or 2+ years of professional experience with machine learning with an advanced degree in a relevant field
• 1+ year of professional experience working directly with external customers to scope out build machine learning models, tools, or services
• Expertise in modern machine learning frameworks and technologies (e.g. PyTorch, Transformers, Scikit-learn, NumPy, Pandas), and an obsession with thorough ML evaluation
• Experience building and maintaining large scale, production data pipelines for machine learning applications
• Ability to work in a fast-paced environment and strong technical communication skills

The salary range for our Tier 1 locations of San Francisco, Seattle, Los Angeles & New York is $140,000.00 - $200,000.00. All offers include equity compensation in the form of employee stock options.