Staff Applied AI Engineer - Enterprise AI Solutions
Snorkel AI · New York City, NY (Hybrid); San Francisco, CA (Hybrid); United States (Remote)
About this role
**About Snorkel** Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! --- **The Role** As an **Applied AI Engineer**, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to deliver solutions to our customers. You’ll work directly with customers to understand their business and technical needs and design and deliver AI solutions to solve them. You’ll also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel’s next generation of AI tooling. This role is ideal for someone who enjoys solving complex problems, bridging AI technology and business value, staying current with AI research, and standardizing bespoke solutions into internal recipes—while staying naturally curious about the infrastructure that underpins the Applied AI stack end-to-end. --- **Main Responsibilities** - Partner with customers to build and deploy impactful Gen AI and ML solutions—from use case scoping and data exploration to model development and deployment. - Develop and implement state-of-the-art AI systems such as **retrieval-augmented generation (RAG)**, **fine-tuning pipelines**, **prompt engineering recipes**, and **agentic workflows**. - Create augmented real-world datasets and comprehensive evaluation workflows to ensure **model reliability, transparency, and stakeholder trust** (data- and evaluation-first mindset required). - Forge and manage relationships with customers’ leadership and stakeholders to ensure successful development and deployment. - Collaborate with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup. - Standardize solutions with other Applied AI Engineers and contribute to internal tooling and best practices. - Lead stakeholder education on quantitative capabilities—helping stakeholders understand strengths/weaknesses and which problems are best suited for Snorkel AI. - Serve as the voice of customers for new AI paradigms and share customer feedback with product teams. - Conduct one-to-few and one-to-many enablement workshops for customers considering or already using Snorkel AI. - Travel: **up to 25% annually**. --- **Preferred Qualifications** - B.S. in a quantitative field (Computer Science, Engineering, Mathematics, Statistics) or comparable experience. - **3+ years** of customer-facing experience designing and implementing AI/ML solutions. - Strong **Python** skills and software engineering fundamentals (modular design, testing, profiling, packaging), plus experience with type validation/typed modeling (e.g., **pydantic**), type-safe systems (e.g., **mypy**), testing (e.g., **pytest**), packaging/environment config (e.g., **poetry**), API/service frameworks (e.g., **FastAPI**), serialization/structured data (e.g., **msgspec**), and ML orchestration tooling (e.g., **Ray**, **Airflow**). - Expertise across t
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