Lead Applied AI & Machine Learning Engineer

What you'll do

• Build and deploy generative AI, agentic AI, and LLM solutions; develop context engineering and intelligent workflow approaches.
• Lead enterprise semantic modeling, ontology governance, and integration patterns across data and application systems.
• Build model lifecycle pipelines and frameworks, implement responsible AI controls, and mentor engineers and data scientists.

What they ask for

• Master’s degree in a data science-related discipline and eight years of industry experience, or a PhD in a data science-related discipline.
• Demonstrated experience developing and deploying machine learning and generative AI solutions using Python.
• Experience writing production-quality code and building automated tests, including unit tests, and continuous integration pipelines.
• Experience building and managing data pipelines and processing workflows for analytics and machine learning.

Nice to have

• Experience designing or governing semantic models and ontologies.
• Experience with retrieval-augmented generation, tool use, and LLM evaluation strategies.

Tools

Python, large language models, application programming interfaces (APIs)

AI focus

Generative AI, agentic AI, LLM applications, context engineering, ontology-driven intelligent workflows, model lifecycle operations, and responsible AI.