Machine Learning Engineer, Research

PhysicsX is a deep-tech company of scientists and engineers, developing machine learning applications to massively accelerate physics simulations and enable a new frontier of optimization opportunities in design and engineering. Born out of numerical physics and proven in Formula One, we help our customers radically improve their concepts and designs, transform their engineering processes and drive operational product performance. We do this in some of the most advanced and important industries of our time – including Space, Aerospace, Medical Devices, Additive Manufacturing, Electric Vehicles, Motorsport, and Renewables. Our work creates positive impact for society, be it by improving the design of artificial hearts, reducing CO2 emissions from aircraft and road vehicles, and increasing the performance of wind turbines.

We are a rapidly growing company but prefer to fly under the radar to protect our customers’ confidentiality. 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 (even if you don't tick all the boxes).

What you will do

• Work intimately with our simulation engineers and research scientists to develop an understanding of the physics and engineering challenges we are solving.
• Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
• Transform prototype implementations to robust production-grade implementation of models.
• Explore distributed training architectures and federated learning capacity.
• Create analytics environments and resources in the cloud or on-premise, spanning data engineering and science.
• Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
• Work at the intersection of data science and software engineering to translate the results of our R&D 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

• Enthusiasm about using machine learning for science and engineering, and especially in scaling such solutions to real-world settings.
• Degree (Master's/Doctorate) in computer science, software engineering or equivalent.
• Experience scaling ML models, both in compute and data storage.
• Federated learning experience is a bonus.
• 1+ year of experience in a data-driven role, with exposure to:

• 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., PyTorch, MLFlow, JAX).
• Distributed computing frameworks (e.g., Spark, Dask).
• Cloud platforms (e.g., AWS, Azure, GCP) and HP computing.
• Containerization and orchestration (Docker, Kubernetes).

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.
• 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 such as generous vacation and parental leave, complimentary office food, as well as fun outings and events.
• Work in a flexible setting, at our lovely London Shoreditch office, and a good proportion from home if so desired. Get the opportunity to occasionally visit our customers' engineering sites and experience first-hand how our work is transforming their ways of working.
• Use first-class equipment for working in-office or remotely, including HPC.

We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.