Machine learning engineer

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.

• Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments.
• Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
• Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
• Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments.
• Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure.
• Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
• Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.

• You are an experienced problem solver and technical leader who stays anchored to impact.
• You can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
• You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success.
• Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
• With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others.
• You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.

• We operate on a hybrid working model with 3 days in our Shoreditch office.
• Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society.
• 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 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.
• 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.
• 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.