Staff Applied AI Engineer - Enterprise AI Solutions

Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. As an Applied AI Engineer, you'll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them. You will 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.

Responsibilities

Partner with customers to build and deploy Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment; Develop and implement 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; Forge and manage relationships with customers' leadership and stakeholders to ensure successful development and deployment of AI projects; Collaborate with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide project setup; Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices; Lead stakeholder education on quantitative capabilities and what problems are best suited for Snorkel AI; Serve as the voice of customers for new AI paradigms and data science workflows, sharing customer feedback with product teams; Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers; Annual travel up to 25%

Requirements

B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience; 8+ years of customer-facing experience in the design and implementation of AI/ML solutions; Proficiency in Python, including software engineering fundamentals (modular design, testing, profiling, packaging) and modern Python libraries and tools (e.g., pydantic, mypy, pytest, poetry, FastAPI, msgspec, Ray, Airflow); Expertise across the Applied AI stack, including classical ML (e.g., scikit-learn), deep learning (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing (e.g., pandas, Spark), RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration/agent tools (e.g., LlamaIndex, LangGraph, CrewAI); Experience leading strategic, customer-facing initiatives with a focus on teaching and enablement; Outstanding presentation skills to technical and executive audiences; Ability to work in a fast-paced environment and balance priorities across multiple projects

Benefits

Equity