Job Title
Technical Product Manager
Ref #
53996
Date posted
Thursday, September 11, 2025
Country
United Kingdom
Location
Woking
Business area
IT
Department
IT
Position level
4
Working time
Full Time
Contract type
Permanent
Working pattern
37.5 Standard 9:00 - 17:00 (30 min lunch)
What to Expect
We are hiring a Technical Product Manager to join our forward-thinking Digital R&D and AI team. In this role, you will own the end-to-end lifecycle of innovative digital products and platforms that accelerate decision-making and value creation across product design, manufacturing, supply-chain and enterprise functions. Partnering closely with simulation specialists, AI researchers, MLOps engineers and domain stakeholders, you will translate complex business and technical challenges into clear product strategies, measurable road-maps and tangible customer impact. This position offers hybrid working flexibility, with full details shared during the application process.
What You'll Do
Drive stakeholder alignment and storytelling. 
Distil complex technical concepts into compelling narratives, dashboards and decision briefs that secure executive buy-in, budget and 
organisational change.
− Translate priority business and engineering problems and inefficiencies into rigorous ML projects to focus team effort on the highest-value opportunities and drive data-driven decisions across 
design, manufacturing and enterprise operations.
− Define success metrics and experimentation strategy. 
- Specify KPIs and oversee controlled experiments (A/B tests, DoE, causal analyses) to validate hypotheses, quantify value and guide resource allocation, ensuring a demonstrable ROI on digital-AI initiatives.
− Lead cross-functional delivery of AI-powered features. Partner with data scientists, simulation experts, MLOps engineers to scope, sequence and ship scalable digital products, tools, services and APIs 
that meet performance, cost and quality targets.
− Champion data readiness and governance. 
- Work with Data & Knowledge Engineering to shape feature-store requirements, uphold data-quality standards and enable re-usability, compliance and rapid iteration throughout the product lifecycle.
− Own production readiness and reliability. Coordinate with platform and MLOps teams to embed monitoring for latency, drift, bias and SLA adherence; drive incident-response playbooks and continuous 
improvement of service health
Embed ethical-AI and privacy-by-design. Ensure every product requirement and release satisfies safety, regulatory and data protection obligations, proactively managing risk assessments and 
approvals.
− Cultivate a learning culture. Mentor junior product, analytics and engineering colleagues; promote rigorous experimentation, reproducibility and knowledge-sharing that scales team capacity over time.
What You'll Bring
Business Knowledge
− Proven insight into how AI-powered digital products unlock value across automotive design, manufacturing, supply-chain and 
enterprise operations, with a clear view of commercial and operational KPIs.
− Fluency in data-driven decision-making and the economics of cloudnative, analytics-first solutions (build vs. buy, TCO, time-to-value).
− Working knowledge of enterprise AI-governance and policy frameworks (e.g., responsible-AI principles, model-risk management, EU AI Act) and a track record of converting them into concrete 
product requirements, approvals and release controls.
− Awareness of the automotive regulatory landscape (safety, functional-safety, data-protection) that shapes product requirements and go-to-market timelines
Essential Functional / Technical Skills
− Degree (or equivalent experience) in Engineering, Computer Science, Data Science or a related quantitative field, plus formal or on-the-job product-management training (e.g., Pragmatic, AIPMM, Scrum-PO).
− 3-5 years managing the end-to-end lifecycle of digital or AI/ML products in complex, data-rich domains—ideally in manufacturing or mobility tech.
− Expertise in agile product development (Scrum/Kanban), backlog curation and user-story writing; hands-on with tools such as Jira/Linear, Confluence/Notion and Git.
− Working knowledge of ML engineering concepts—model lifecycle, MLOps pipelines, data governance, drift/bias monitoring—enabling credible collaboration with Data Scientists and SRE/MLOps teams
Familiarity with cloud platforms (AWS / Azure), container orchestration (Docker, Kubernetes) and API design best practices; 
able to translate technical constraints into product decisions.
− Comfortable querying data with SQL and validating JSON / REST responses; able to craft quick analyses or dashboards in Power BI, Looker, Plotly or similar to inform prioritisation.
− Experience designing and analysing A/B tests, DoE or causal-impact experiments to quantify feature value and guide roadmap trade-offs.
− Demonstrated ability to run cross-functional ceremonies (kick-offs, sprint reviews, release readiness) and to shepherd epics from discovery through launch and adoption tracking
Personal Attributes / Competencies
− Analytical storyteller who converts complex technical insights into crisp narratives, visuals and executive-ready recommendations.
− Stakeholder whisperer—adept at aligning engineering, design, operations and leadership around shared goals, trade-offs and success metrics.
− Bias for action with strong organisational rigour: you unblock teams, anticipate risks and keep multiple work-streams moving in parallel.
− Advocate for ethical AI and privacy-by-design, ensuring every release meets safety, security and compliance standards.
− Growth mindset; quick to learn emerging tools (LLM ops, gen-AI tooling) and to coach junior colleagues on product best practices.
Desirable Expertise
− Exposure to Generative AI (text, vision or 3-D) and its integration into customer-facing workflows.
− Familiarity with automotive telemetry (CAN-bus), PLM/ERP datasets or high-fidelity simulation outputs used in design-for-manufacture loops.
− Experience with Bayesian optimisation, reinforcement-learning driven control systems or graph data products in an industrial 
context.
− Track record of community engagement—conference talks, open source contributions, standards working groups—demonstrating 
thought leadership in AI product development
What We'll Do for You

We offer a wide – ranging benefits package, which includes:

  • Structured career development framework
  • 25 days’ holiday, plus bank holiday. Annual buy & sell up to five days
  • Enhanced company pension scheme
  • Discretionary annual bonus award
  • Private medical insurance and health cash plan
  • Life assurance benefit
  • Ability to apply for a sabbatical of up to one year after only two years’ service
  • Benefits you can adapt to your lifestyle, such as discounted shopping
  • Generous parental leave policies
  • A range of wellbeing initiatives, such as employee assistance programme and free financial & mortgage advice
Who Are We?

No restraints. No limitations. We don’t simply push boundaries. We completely rethink them. McLaren Automotive exists to create breath-taking performance road cars.

It takes a community to do what we do. A diverse group of people with many areas of expertise, united by their passion to deliver visionary products and set new benchmarks. 

McLaren Automotive commits to equal opportunity for all. Diversity, Equality and Inclusion is at the heart of our impact, it drives our innovation and enables us to truly create something special. Join us on our journey. 

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