Senior Product Manager, AI/ML Platform Products
Listed on 2026-01-06
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IT/Tech
AI Engineer
Site Name: 200 Cambridge Park Drive, Upper Providence
Posted Date:
Dec 4 2025
The Onyx Research Data Tech organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step change in our ability to leverage data, knowledge, and prediction to find new medicines. We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and Dev Ops, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:
- Building a next-generation data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics”
- Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent
- Aggressively engineering our data at scale to unlock the value of our combined data assets and predictions in real-time
Onyx Product Management is at the heart of our mission, ensuring that everything from our infrastructure, to platforms, to end-user facing data assets and environments is designed to maximize our impact on R&D. The Product Management team partners with R&D stakeholders and Onyx leadership to develop a strategic roadmap for all customer-facing aspects of Onyx, including data assets, ontology, Knowledge Graph / semantic search, data / computing / analysis platforms, and data-powered /LLM-enabled applications.
We are seeking an experienced Senior Product Manager to lead the strategy and delivery of AI/ML platform products – the core platform that powers AI/ML model training and deployment across GSK R&D. This role is central to establishing a unified, scalable, and governed enterprise approach to AI/ML, ensuring that R&D teams can efficiently build, evaluate, and operationalize models and ultimately deliver new medicines for our patients.
Key responsibilities include:Ownership & Strategy
- 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.
Customer & Stakeholder Engagement
- 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.
Product Planning & Delivery
- 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.
Platform Integration & Governance
- 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.
Launch, Adoption & Optimization
- 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.
Basic Qualifications:
We are looking for professionals with these required skills to achieve our goals:
- PhD + 2 years, Masters + 4 years, or Bachelors + 6 years
- 4+ years of experience in product management with a proven track record of delivering AI‑powered applications (0‑to‑1 or scaled products) that solve concrete business or scientific problems in an enterprise or regulated environment.
- Experience defining product strategy for modern applications, including experience working closely with data scientists, ML engineers, and domain experts to…
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