Machine Learning Product Manager – Hybrid, Maternity Cover

Oxford Nanopore Technologies; Oxford; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

Oxford Nanopore Technologies is seeking a Machine Learning Product Manager to lead AI/ML software strategy in a hybrid Oxford setting. You will partner with ML researchers, software engineers, bioinformaticians and customers to shape roadmaps that balance scientific innovation with practical delivery.

The role spans concept through launch, with an emphasis on data-driven decisions, KPI development and risk mitigation while ensuring regulatory compliance and quality standards are upheld.

Qualifications

• Proven experience taking AI/ML software from concept to launch.
• Strong understanding of the ML lifecycle: data, training, validation, deployment.
• Experience working with software engineering and ML research teams.

Responsibilities

• Define strategy and roadmap for AI/ML software across the platform.
• Lead AI/ML software lifecycle from concept through iteration and release.
• Translate market requirements into clear product specs with SMEs.
• Prioritise features and manage the product backlog in sprints.
• Collaborate with R&D, marketing, sales and support for launches.
• Analyze usage, feedback and trends to drive KPIs and decisions.
• Provide technical guidance and mitigate risks across development.
• Ensure software products meet QMS and regulatory standards.

Skills

AI/ML product lifecycle

Cross-functional collaboration

Agile software development

Data-driven decision making

Stakeholder communication

R&D collaboration

Education

Bachelor's/Master’s/PhD in CS or related fields

Tools

Basecalling tools

Job description

Oxford Nanopore Technologies is seeking a Machine Learning Product Manager to lead AI/ML software strategy in a hybrid Oxford setting. You will partner with ML researchers, software engineers, bioinformaticians and customers to shape roadmaps that balance scientific innovation with practical delivery.

The role spans concept through launch, with an emphasis on data-driven decisions, KPI development and risk mitigation while ensuring regulatory compliance and quality standards are upheld.