Senior Machine Learning Engineer / Data Scientist in Cambridge

About Secondmind

Secondmind builds data‑efficient engineering AI software that helps teams make better design and performance optimisation decisions faster. Our product reduces simulation and testing requirements without compromising quality, accelerating development and enabling more sustainable outcomes. Our positive working culture is founded on a collaborative environment that encourages teamwork and innovation. We foster open communication and cross‑functional collaboration, enabling diverse teams to work together to solve complex challenges. Our flexible workplace plan ensures a healthy work‑life balance, accommodating various working styles and personal needs, whether through remote work options or adaptable schedules. We also prioritise personal and professional growth by offering development opportunities, including training and mentorship. This nurturing environment empowers our employees to thrive, continuously learn, and contribute meaningfully to our mission of advancing system design and calibration with our data‑efficient machine learning solutions.

Founded in 2016 and supported by investors such as Mazda Motor Corporation, Amadeus Capital, Atlantic Bridge and Cambridge Innovation Capital, Secondmind was recently recognised with the Automotive Testing Technology International ‘Alternative Powertrain Test Innovation of the Year Award 2024’; selected for the Tech Nation Future Fifty scale‑up programme, and named by Bloomberg as one of the UK’s 25 Startups to Watch 2024.

About the role

We are looking for an experienced problem solver who is passionate about building practical solutions that help customers make better engineering decisions. Our product is already changing the way engineers work by bringing advanced machine learning into their design and calibration workflows. That often means customers need real technical depth alongside them; someone who can help them frame their problems, diagnose why a model isn’t behaving as expected in their specific context, and guide them through new ways of working. A key part of the role is feeding what you learn from these engagements back into the product to shape how it evolves. Secondmind is a product company, not a consultancy. Our software integrates directly with real test benches and simulation toolchains, applying cutting‑edge probabilistic modelling and active learning to solve complex engineering problems. You will work closely with our research team to productionise ideas that often haven’t been published yet, turning frontier ML into reliable product capabilities. If that combination of research, engineering rigor, and real‑world impact excites rather than daunts you, you’ll thrive here. Nobody here has all the answers alone. We work in tight‑knit, cross‑functional squads where research, engineering, and product expertise come together to solve hard problems. To succeed, you need to be comfortable operating with significant autonomy in the face of ambiguity, working things out for yourself, and knowing when and how to draw on the people around you.

What will you be responsible for?

• Developing and integrating ML capabilities: Building the ML capabilities that power the product. That could mean collaborating with our research team to productionise novel ideas that are ahead of the published literature, evaluating and integrating established methods, or developing your own algorithms. In all cases, the goal is to make them reliable and maintainable within a complex, integrated codebase.
• Customer guidance: Helping customers frame their engineering problems in terms our product can address, and guiding them through new ways of working.
• Diagnosing complex issues: When a customer’s data goes into the product and something isn’t right, you are the person who can unpick whether it’s a data quality issue, unexpected model behaviour, a configuration problem, or a genuine bug. This requires a deep understanding of both the ML and the production system.
• Shaping product direction: You sit at the intersection of what our researchers envision, what our customers actually need, and what is realistic to build and maintain in production. You will use that perspective to help shape where the product goes next.
• Codebase stewardship: Contributing to and maintaining a production codebase that interfaces with real test benches and simulation toolchains. Writing code that is clear, tested, and ready for others to build on.

What skills, experience, and qualifications do you need to succeed in this role?

Essential

• Strong theoretical and practical foundations in machine learning. You understand the fundamentals deeply, not just how to call a library, and you have real experience applying them to solve problems.
• Proficiency in Python and comfort working in a large, production‑grade codebase (not just notebooks and scripts).
• Hands‑on experience with at least one major ML framework (e.g. TensorFlow, PyTorch).
• The ability to thrive in complexity and ambiguity. You can take an ill‑defined problem, break it down, and make progress without waiting for instructions.
• Excellent judgement about when to work independently and when to ask for help, with the interpersonal skills to draw out the knowledge of domain experts, researchers, and engineers around you.

Desirable

• Familiarity with automotive, manufacturing, or other engineering sectors. You don’t need to be a domain expert, but an appreciation for how engineers work and the kinds of problems they face goes a long way.
• Experience working directly with customers or external stakeholders in a technical capacity.
• Strong foundations in probabilistic modelling (Gaussian processes, Bayesian methods, uncertainty quantification) and practical experience applying these techniques to real problems.
• Experience with active learning, Bayesian optimisation, or design of experiments.
• Familiarity with TensorFlow. Our stack builds on GPflow and Trieste, open‑source libraries that we actively maintain and develop.
• Experience productionising ML models. You are comfortable in taking research‑grade code and making it reliable, performant, and maintainable in a CI/CD‑driven environment.

Our culture – What we can offer you

We offer a working environment that is inclusive, stimulates innovation and continuous learning, and that thrives on growth and change. Our culture is underpinned by our values; they are what we stand for and part of our DNA. They help us attract and retain the right talent and customers, help us make the right decisions and clarify how we should all behave and treat one another.

Our values

• Delight every customer (Customers)
• No bar too high (Excellence)
• Give more than take (Sustainability)
• Make the impossible, possible (Innovation)
• Celebrate differences, act as one (Inclusion)

Benefits

• Competitive salary – reviewed annually
• 25 days annual leave, plus statutory bank holidays
• TGIF: The last Friday of every month is a half day for our employees
• Enhanced family leave policies
• Salary Sacrifice Pension Scheme
• Life Assurance of 4× salary
• Private Medical Insurance
• Eyecare Policy
• Dental Cash Plan
• Stock Options (where applicable)
• Free 24‑hour access on‑site gym
• Discount Shopping & Wellbeing Platform
• Employee Assistance Programme
• Values Award Scheme
• Cambridge Botanic Garden membership
• Social events, game nights and sports groups

Equal Opportunities

We are an equal opportunities employer, and aim to ensure all candidates are treated equally and fairly through the application process and beyond. We actively encourage applicants from under‑represented backgrounds, and encourage our people to bring their authentic, original, and best selves to work. If you require assistance or an accommodation through the interview process due to a disability, to apply for one of our roles, please contact hr@secondmind.ai.