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Salary: USD 230,000 - 360,000 / annual
Snorkel AI is a frontier AI data lab founded out of Stanford in 2019, helping teams build datasets, benchmarks, evaluations, and custom solutions for high-performing frontier and agentic AI systems. The company combines technology with research-driven AI data development to serve leading AI labs and enterprises.
As a Staff Applied AI Engineer, you will research and deploy state-of-the-art generative AI and machine learning solutions directly with customers. You'll partner with customers end-to-end—from use case scoping and data exploration through model development and deployment—designing custom approaches using cutting-edge tools to deliver real business value. Your work will inform the evolution of Snorkel's platform and tooling.
Key responsibilities include:
- Partnering with customers to build and deploy impactful Gen AI and ML solutions, designing custom approaches and delivering real business value
- Developing and implementing state-of-the-art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes, and agentic workflows
- Creating augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust
- Managing relationships with customers' leadership and stakeholders to ensure successful project development and deployment
- Collaborating with pre-sales Solutions and Product teams to map customer needs to existing capabilities and guide project setup
- Standardizing solutions with other Applied AI Engineers and contributing to internal tooling and best practices
- Leading stakeholder education on quantitative capabilities and helping them understand the strengths and weaknesses of different approaches
- Serving as the voice of customers for new AI paradigms and data science workflows, sharing feedback with product teams
- Conducting one-to-few and one-to-many enablement workshops to transfer knowledge to customers
- Travel up to 25% annually
This role is ideal for someone who enjoys solving complex problems, bridging AI technology with business value, working directly with customers, staying current with AI research, and standardizing bespoke solutions into reusable recipes.
QUALIFICATIONS:
- B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience
- 3+ years of customer-facing experience in the design and implementation of AI/ML solutions
- Proficiency in Python with strong software engineering fundamentals (modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries including pydantic, mypy, pytest, poetry, FastAPI, msgspec, and orchestration tooling (Ray, Airflow)
- Expertise across the Applied AI stack: classical ML libraries (scikit-learn), deep learning frameworks (PyTorch), foundation-model ecosystems (Hugging Face Transformers), vector/embedding tooling (FAISS), data processing frameworks (pandas, Spark), retrieval/RAG tooling (Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration/workflow/agent authoring tools (LlamaIndex, LangGraph, CrewAI)
- Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong 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
