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.
Note:Â We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.
What you will doÂ
Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.
Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
Transform prototype model implementations to robust and optimised implementations.
Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services.
Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute.
Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
Own Research work-streams at different levels, depending on s...