Machine Learning Engineer

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About the role

About us Re-architecting Engineering for the Age of Intelligence 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 Enginee r 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 ope

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