PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

• Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
• Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
• Explore and manipulate 3D point cloud & mesh data
• Own the delivery of technical workstreams
• Create analytics environments and resources in the cloud or on premise, spanning data engineering and science
• Identify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for success
• Work at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and products
• Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption

• Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods) to real-world engineering applications, with a focus on driving measurable impact in industry settings. Experience in ML/Computational
• Statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes) is encouraged.
• A track record of scoping and delivering projects in a customer facing role
• 2+ years experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
• Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)
• Distributed computing frameworks (e.g., Spark, Dask)
• Cloud platforms (e.g., AWS, Azure, GCP) and HP computing
• Containerization and orchestration (Docker, Kubernetes)
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
• Excellent collaboration and communication skills - with teams and customers alike
• A background in Physics, Engineering, or equivalent

• Equity options share in our success and growth.
• 10% employer pension contribution invest in your future.
• Free office lunches great food to fuel your workdays.
• Flexible working balance your work and life in a way that works for you.
• Hybrid setup enjoy our new Shoreditch office while keeping remote flexibility.
• Enhanced parental leave support for lifes biggest milestones.
• Private healthcare comprehensive coverage
• Personal development access learning and training to help you grow.
• Work from anywhere extend your remote setup to enjoy the sun or reconnect with loved ones.