Senior Product Manager, AI/ML Platform Products

Role Summary

Senior Product Manager to lead the strategy and delivery of AI/ML platform products—the core platform powering AI/ML model training and deployment across GSK R&D. This role centralizes a unified, scalable, and governed enterprise approach to AI/ML, enabling R&D teams to efficiently build, evaluate, and operationalize models to advance medicine development.

Responsibilities

• Own and drive the product vision, roadmap, and adoption of the AI/ML Platform, delivering core capabilities for model training, fine-tuning, evaluation, deployment, monitoring, and lifecycle management.
• Define the strategic direction for foundational AI/ML tooling and ensure platform capabilities meet the needs of diverse R&D model development workflows and scientific applications.
• Conduct ongoing customer discovery with scientists and AI/ML practitioners to identify emerging needs and translate them into actionable product requirements.
• Lead technical product discussions with engineering and scientific leaders to clarify objectives and shape platform direction.
• Collaborate with stakeholders to define platform features, requirements, and success criteria aligned with scientific use cases and business goals.
• Drive agile product execution with engineering and program teams, owning prioritization, backlog management, and delivery of high-quality platform releases.
• Ensure seamless integration with the Data Platform to enable shared data standards and consistent data/model lifecycle management.
• Coordinate and align product roadmap with R&D platforms to ensure interoperability, governance alignment, and a unified enterprise data, compute, AI, and application ecosystem.
• Lead platform launches and change-management activities to ensure clear communication, training, and successful adoption across R&D.
• Monitor platform usage and performance, analyze feedback and telemetry, and drive continuous improvements to enhance usability, reliability, and scientific impact.

Qualifications

• Required: PhD + 2 years, Masters + 4 years, or Bachelors + 6 years
• Required: 4+ years of experience in product management with a proven track record of delivering AI-powered applications that solve concrete business or scientific problems in an enterprise or regulated environment
• Required: Experience defining product strategy for modern applications, including collaboration with data scientists, ML engineers, and domain experts to shape model requirements and end-to-end workflows
• Required: Experience with AI/ML fundamentals, including model development lifecycles, data pipelines, feature engineering, and MLOps practices, and ability to translate business needs into technical requirements
• Required: Experience integrating AI models into user-facing products, including UX workflows, decision-support tools, automation flows, or scientific applications used by R&D teams
• Required: Experience driving adoption, change management, and measurable business impact for AI solutions across diverse R&D user groups
• Preferred: Direct product management experience building and launching AI/ML-powered applications, including decision-support tools or predictive modeling used by R&D, clinical, or operational teams
• Preferred: Hands-on experience collaborating with data scientists or ML engineers to define problem statements, model requirements, evaluation approaches, and ML deployment workflows
• Preferred: Familiarity with modern ML/transformer architectures and evaluating trade-offs between off-the-shelf models, open-source models, and domain-specific fine-tuned models
• Preferred: Experience developing products that analyze or surface complex, unstructured scientific data (biomedical text, omics data, imaging, knowledge graphs)
• Preferred: Working knowledge of bioinformatics, computational biology, or cheminformatics, and vision for AI-driven acceleration of research workflows
• Preferred: Product experience shaping end-to-end ML-driven workflows (feature pipelines, model serving, monitoring, human-in-the-loop UX)
• Preferred: Proficiency with product management and collaboration tools (Confluence, Jira, Miro, Monday, Notion) for roadmapping and cross-functional planning
• Preferred: Experience in life sciences or biopharma R&D is a strong plus