Staff Applied AI Engineer - Enterprise AI Solutions

About the Role

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 that become part of Snorkel's next generation of AI tooling.

Main Responsibilities

• Partner with customers to build and deploy impactful Gen AI and machine learning 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.
• Forge and manage relationships with customers' leadership and stakeholders to ensure successful development and deployment of AI projects.
• Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful 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, helping them understand the strengths and weaknesses of different approaches.
• Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams.
• Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.
• Annual travel up to 25%.

Preferred Qualifications

• 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 strong grounding in software engineering fundamentals (modular design, testing, profiling, packaging) and modern constructs/libraries (pydantic, mypy, pytest, poetry, FastAPI, msgspec, Ray, Airflow).
• Expertise across the Applied AI stack, spanning classical ML libraries (scikit-learn), deep learning frameworks (PyTorch), foundation-model ecosystems (Hugging Face Transformers), vector/embedding tooling (FAISS), data processing (pandas, Spark), retrieval/RAG tooling (Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and agent authoring tools (LlamaIndex, LangGraph, CrewAI).
• Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders.
• Outstanding presentation skills to technical and executive audiences.
• Ability to work in a fast-paced environment and balance priorities across multiple projects at once.