Technical Product Manager

• Proven experience taking AI/ML models and software products from concept through launch and iterative release.
• Strong understanding of the complete machine learning lifecycle, including data collection, model training, validation, deployment, and monitoring.
• Direct experience working closely with software engineering and machine learning research teams.
• Demonstrated track record of defining product roadmaps using customer insights and quantitative data.
• Excellent written and verbal communication skills, with the ability to translate complex technical concepts across diverse stakeholders.
• Collaborative and flexible approach to building effective relationships across multidisciplinary teams.

• Familiarity with DNA/RNA sequencing technologies and bioinformatics workflows.
• Hands-on experience within Agile software development frameworks.
• A genuine passion for technology, innovation, and the potential of nanopore sequencing.

Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and abilities to perform the duties of the job.

Machine Learning Product Manager

• Product Strategy & Roadmap: Manage and communicate the product vision, strategy, and roadmap for AI/ML-powered software (including basecalling and bioinformatics tools) based on customer needs, scientific evidence, and business goals.
• Lifecycle Ownership: Lead and own AI/ML software through all stages of the product lifecycle: concept, design, development, launch, and iteration.
• Requirement Translation: Collaborate with subject matter experts in ML, software, bioinformatics, and genomic/transcriptomic applications to convert market requirements into clear product specifications.
• Product Execution: Prioritise features and manage the product backlog effectively within agile development cycles.
• Cross-Functional Collaboration: Partner with R&D, marketing, sales, and support teams to ensure smooth and successful product launches.
• Data-Driven Insights: Analyse usage data, customer feedback, and market trends to establish key performance indicators (KPIs) and drive data-informed product decisions.
• Technical Guidance & Risk Mitigation: Serve as a product advisor to ensure alignment on technical capabilities between R&D and commercial teams, while identifying and mitigating technical risks throughout development.
• Quality & Compliance: Ensure all software products are developed in compliance with applicable Quality Management Systems (QMS) and regulatory standards, supporting the generation and maintenance of key documentation.

Full-Time, Fixed-Term Contract (Maternity Cover)

Oxford, UK (Hybrid)

Product Management

Director, Software Product Management

Oxford Nanopore has developed a new generation of nanopore-based sensing technology for faster, information-rich, accessible and affordable molecular analysis. The technology is used to understand and characterise the biology of humans, animals, plants, bacteria, viruses, and diseases such as cancer. By enabling biological insights, we strive to improve life on Earth and beyond.

We are seeking a highly motivated and detail-oriented Machine Learning Product Manager to join our Product Management team on a Fixed-Term Contract (Maternity Cover).

In this role, you will collaborate with both technical and commercial stakeholders to define the strategy and product roadmap for AI/ML capabilities across Oxford Nanopore's software ecosystem. Working closely with ML researchers, software engineers, bioinformaticians, support teams, marketing, and customers, you will bridge scientific innovation and scalable product delivery-balancing customer needs, commercial priorities, and cutting-edge machine learning technology.

The Ideal CandidateQualifications & Education

• Bachelor's, Master's, or PhD in Computer Science, Bioinformatics, Data Science, Engineering, Life Sciences, or a related discipline.