Applied AI and ML Lead, Generative AI

What you'll do

• Build generative AI, agentic AI, and LLM solutions in Python from concept to production deployment.
• Design context engineering approaches to improve model accuracy, latency, reliability, and user experience.
• Lead enterprise semantic modeling strategy including ontology standards, governance practices, and lifecycle management.
• Create scalable ontologies with domain experts to represent business entities, relationships, and constraints.
• Define semantic integration patterns across data pipelines, APIs, and data contracts to resolve conflicts.
• Establish a unified semantic layer to enable trusted analytics across BI, machine learning, and transactional systems.
• Develop intelligent workflows and AI agents using ontology-driven context and orchestration techniques.
• Build and maintain pipelines for model training, evaluation, optimization, monitoring, and MLOps.

What we're looking 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.
• Proven ability to write and maintain production-quality code with documentation and maintainable design patterns.
• Experience building automated testing practices, including unit tests, and implementing continuous integration pipelines.
• Experience building and managing data pipelines and processing workflows for analytics and machine learning use cases.
• Strong scientific thinking and structured problem-solving skills, including hypothesis-driven analysis and metric definition.
• Strong written and verbal communication skills to explain complex concepts to technical and non-technical stakeholders.
• Experience with semantic models, RAG, tool use, and responsible AI techniques (preferred).