Machine Learning Engineer

PhysicsX Ltd.; City Of London; Hybrid; GBP 55,000 - 90,000; Full time

Benefits offered by this job

Equity options

10% employer pension contribution

Free office lunches

Enhanced parental leave

YellowNest nursery scheme

25 days of Annual Leave (+ Public H ol

Private medical insurance

Wellhub Subscription

Eye tests

Personal development

Employee Assistance Programme (EAP)

Bike2Work scheme and Season ticket

Job summary

PhysicsX Ltd. in London is seeking a Machine Learning Engineer in Delivery to design, build and deploy production‑grade ML tools that help customers make better engineering decisions.

You will work with simulation engineers and data scientists, handle 3D data, and travel to client sites across NA, Europe, and Asia several weeks each quarter. The role blends data science with software engineering and offers a hybrid work model from our Shoreditch office.

Qualifications

• Minimum 1 year industry experience post Masters or PhD.
• Proven ability to design and deploy ML pipelines in production.
• Experience with 3D point-cloud/mesh data and geometry-aware modeling.

Responsibilities

• Design, build and test robust, scalable data/ML pipelines.
• Productionise ML models with validation and error analysis.
• Manipulate 3D point-cloud/mesh data using geometry-aware techniques.
• Collaborate with simulation engineers to integrate models into simulations.
• Engage with customers, onboard users and co-develop solutions.
• Travel to customer sites worldwide 3–4 weeks per quarter.

Skills

ML pipelines

Production ML

3D data

Python

Cloud/on-prem

Customer engagement

Data science

Geometry AI

Cross-functional

Education

Master's degree

PhD

Tools

Python

PyTorch

TensorFlow

AWS

GCP

Docker

Job description

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.

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 science 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.

• 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…

We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.

We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.