Artificial Intelligence​/Machine Learning; AI​/ML) Capability Engineering Team Lead

The Artificial Intelligence / Machine Learning (AI/ML) Capability Engineering Team Lead supervises a cross-functionally embedded team of AI/ML Engineers and Data Scientists developing innovative AI Natural Language Processing (NLP) and Agentic AI capabilities for therapeutic research and development. Working with partners across the R&D pipeline and software technology stack, you will lead AI initiatives, influence AI strategy, and supervise a team of talented individuals.

The models and pipelines that you and your team develop will help solve real-world problems and improve patient outcomes.

• Building, deploying, and publishing innovative and robust AI methods and agentic workflows that drive impact in areas such as AI machine translation, content generation and document drafting, workflow optimization, large-scale data enrichment, literature mining, target and biomarker prioritization, and representation learning (e.g., molecular design).
• Partnering with stakeholders and product teams to ideate, design, build, and iteratively improve impactful solutions.
• Rigorously evaluating and optimizing machine learning and AI workflows using standard and novel techniques, as well as developing human-in-the-loop AI approaches.
• Having the freedom to propose areas of focus and solutions to explore.
• Collaborating cross-functionally with experts across the R&D pipeline and across modalities of informatics and AI/ML work, including image processing, bioinformatics, representation learning, decision sciences, and more.
• Tracking and helping to adhere to the developing landscape of AI regulations and internal policies, such as for data privacy and risk mitigation.
• Staying up-to-date on the latest innovations in AI/ML and Agentic AI.
• Using AI coding assistants in innovative and responsible ways.
• Presenting plans and results to scientific and IT leadership and providing input on strategic planning.
• Supervising, mentoring, and recruiting talented AI/ML engineers and other personas.

• Excellent technical and non-technical communication, planning, teamwork, and leadership skills.
• The ability to critically evaluate new problems, as well as AI/ML solution architecture and implementation.
• A strategic mindset, including the ability to envision how AI/ML and software solutions may generalize to new areas of application.
• Deep understanding of modern LLM and Agentic architectures, including retrieval-augmented generation (RAG), tool calling / Model Context Protocol (MCP), structured extraction, and agent orchestration.
• Fluency in Python programming, version control and collaboration with Git, environment management (e.g., uv, Docker), and at least one ML framework (e.g., Pytorch, vLLM).
• Excellent statistical analysis skills (e.g., a strong understanding of the implications of class imbalance).
• Experience with scalable engineering frameworks such as Apache Spark and orchestrator frameworks such as Airflow.
• Experience with Agentic AI protocols and standards such as MCP, A2A, and A2UI and with building production-ready software and AI solutions.
• Experience with harness optimization approaches (e.g., auto‑research).
• Experience with AI/ML model deployment and operations, as well as modern software deployment standards (e.g., Dev Ops and CI/CD practices).
• Experience with agentic system development (e.g., Lang Graph), text processing (e.g., regular expressions, information retrieval, search systems), semantic engineering (e.g., RDF), and/or data engineering.
• Familiarity with enterprise AI governance, data privacy boundaries, validation, fairness, and related ethical AI topics.
• A passion for technology, science, biomedicine,…