Applied Artificial Intelligence Engineer (Enterprise Solutions)

Join Snorkel, a leading company in the field of Applied AI. As an Applied AI Engineer, you will work directly with customers to understand their business and technical needs, design and deliver AI solutions, and help define Snorkel's Applied AI tooling. You will have the opportunity to develop and implement state-of-the-art AI systems, create augmented real-world datasets, and forge relationships with customers' leadership and stakeholders. This position offers a competitive salary, comprehensive benefits, and the chance to work with a global team.

• Research and utilize state-of-the-art Generative AI and machine learning techniques to deliver solutions to customers.
• Work directly with customers to understand their business and technical needs, and design and deliver AI solutions to solve them.
• Help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities.
• This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end
• B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience
• Ability to work in a fast-paced environment and balance priorities across multiple projects at once
• Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow)
• Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
• 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
• 3+ years of customer-facing experience in the design and implementation of AI/ML solutions
• Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI)