Machine Learning Engineer
Physicsx
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What learning roles keep asking for: Machine learning (61%), Python (50%), PyTorch (32%), LLMs (28%), Deep learning (22%), AWS (20%), Generative AI (17%), C++ (17%) — counted across their open postings here.
Machine Learning Engineer jobs in the United Kingdom · Machine Learning Engineer jobs in London · Remote Machine Learning Engineer jobs · Machine learning jobs
Physicsx has 6 open roles listed here.
- Staff Backend Software Engineer - GO & Python
- Data Scientist
- Senior Machine Learning Software Engineer, Research
- Senior Machine Learning Engineer
- Senior CFD Engineer - Plasma Specialist
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for learning roles keep coming back to Machine learning, Python, PyTorch, LLMs. Practise those questions before you sit with Physicsx.
Questions you are likely to be asked
- Why do you want to join Physicsx?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
- How would you explain your model's result to someone who is not technical?
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Practise the Machine Learning Engineer at Physicsx interview free →About us
PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
Who We're Looking For
As a Machine Learning Engineer in Delivery, you are a problem solver and builder who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, and you excel at working directly with customers (and often side-by-side with them on-site) to build, deploy and maintain production-grade ML tools that are useful, and used.
You design, build, and test reliable, scalable machine learning pipelines, and you know when to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling. You create analytics environments and resources in the cloud/on-prem that span data science, selecting the right libraries, frameworks and tools while making pragmatic product decisions that set delivery up for success. You thrive at the intersection of data sicence and software engineering, translating project outputs into tooling and products.
With at least 1 year industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re truly excited about growing your technical expertise and are naturally inclined to take ownership of MLE pipelines, continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving customer needs.
This Role
In this role, you’ll work closely with our customers, as well as our team of Simulation Engineers, Data Scientists, and Software Engineers, to understand and define the engineering and physics challenges we are solving.
You’ll build the foundations for successful, impactful solutions by:
- Designing, building and testing data/ML pipelines, that are reliable, scalable and easily deployable in production environment.
- Productionising ML models and surrogates with clear validation, error analysis
- Exploring and manipulating 3D point-cloud and mesh data, applying graph/geometry-aware techniques where appropriate
- Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
- Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co-develop with customers.
- There is a requirement to travel to customer sites in North America, Europe, Asia, Oceania, an average of 3-4 weeks per quarter, where you’ll collaborate closely with customers to build solutions on site.
As the role evolves, there are exciting opportunities for growth as a technical lead, perfect for someone who is driven by taking ownership of more complex projects and leading the direction of future solutions.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!
We operate on a hybrid model, with around three days per week based in our Shoreditch office.
What we offer
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.
Sustainable pace, long-term ambition
Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
And it doesn’t stop there …
🚀 Equity options - share meaningfully in the company you’re helping to build.
🏦 10% employer pension contribution - because investing in future matters.
🍽️ Free office lunches - to keep you energised and focused.
👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
🍼 YellowNest nursery scheme - to help working parents manage childcare costs.
☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.
💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.
👀 Eye tests - because good work depends on good health.
📈 Personal development - dedicated support for learning, development, and leveling up over time.
💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.
🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.
🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.
🔎 Watch this space, we’re continuing to build this as we grow…
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Check my match →Similar open roles
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Listed on arbeitnow · posted 2026-10-14. ApplySarthi collects openings and links to application pages; the role is advertised by Physicsx, not by us.