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. We are about to take the next leap in building out our technology platform and product offering. In this context, we are looking for a capable and enthusiastic machine learning engineer to join our team. If all of this sounds exciting to you, we would love to talk. Note: We do not provide visa sponsorship in the US. Please only apply if you have the right to work in the US. What you will do

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

What you bring to the table

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

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

What we offer

Be part of something larger: Make an impact and meaningfully shape an early-stage company. Work on some of the most exciting and important topics there are. Do something you can be proud of 

Work with a fun group of colleagues that support you, challenge you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields and solve truly challenging problems in science and engineering. If you are similarly capable, caring and driven, you'll find yourself at home here 

Experience a truly flat hierarchy. Voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo 

Work sustainably, striking the right balance between work and personal life.

Receive a competitive compensation and equity package, in addition to plenty of perks