About us

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.

The Role

PhysicsX is building a platform that enables Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The platform handles massive volumes of complex simulation data and enables high fidelity multi physics simulation through AI inference.

We are looking for a Senior (potentially Staff level, depending on the candidate) Software Engineer to join the AI Workbench platform team. This is a software engineering role, not an ML research role. You do not need to be a practising ML engineer, but you do need to be fluent in the language of ML and data platforms, ideally through prior hands on experience with ML platforms or data science work.

The team sits in a highly infrastructure heavy domain without being an infrastructure team itself. A large part of the role is building strong working relationships with the infrastructure team and owning the work that falls in the space between the two, where ownership is not always clearly defined. You will also play a key role in mentoring and developing engineers across the team, some of whom are early career and some mid career.

Note for candidates: PhysicsX is currently going through a team reorganisation. The scope of this role may evolve as team structures settle, and we have kept this description intentionally broad rather than narrowly tailored to today's team shape.

What You Will Do

• Design and build distributed systems, services, and APIs for high dimensional simulation data across the machine learning lifecycle, from data processing and model training to inference services.
• Own work end to end in a domain where responsibilities often sit between the AIWB platform team and the wider infrastructure team, and proactively build the relationships needed to manage that ambiguity well.
• Build tools that enable data scientists and engineers to create automated, robust pipelines for data ingestion and processing, powering active learning loops.
• Architect and integrate storage solutions, data warehouses, and data lakes to handle the demands of complex simulations, multimodal data, and deep learning workloads.
• Deploy and support services across more than one production environment, including cloud and on premises or air gapped customer environments.
• Define system architecture for new capabilities, making trade offs across performance, reliability, cost, and developer experience.
• Author and review Technical Decision Records and contribute to Technology Radar reviews.
• Mentor and support the growth of engineers across the team, including those earlier in their careers, and act as a technical role model.
• Remain genuinely hands on. Writing code stays part of the job at every level, this is not a purely managerial track.
• Communicate clearly and confidently with a wide range of stakeholders and personalities across engineering, delivery, and customer facing teams.