Backend Software Engineer

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.

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.