Software Engineer

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 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.
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.
Own Research work-streams at different levels, depending on seniority.
Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.
Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.
Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
Ability to work autonomously and scope and effectively deliver projects across a variety of domains.
MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following:
Scientific computing;
High-performance computing (CPU / GPU clusters);
Parallelised / distributed training for large / foundation models.
~ 1 years of experience in a data-driven role, with exposure to:
~ scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);
~ Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);
~ AWS, Azure, GCP);
~ building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., C/C++ for computer vision, geometry processing, or scientific computing;
~ software engineering concepts and best practices (e.g., 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 life’s 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.

We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation.