Machine Learning Software Engineer

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 optimisation opportunities in design, engineering, and systems control.

We help our customers fundamentally 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 Renewables & Sustainability, Space, Aerospace, Medical Devices, Additive Manufacturing and Energy. Our work creates positive impact for society, be it by improving the design of artificial hearts, reducing CO2 emissions from aircraft and road vehicles, or increasing the performance of wind turbines. 

The Role

PhysicsX is developing a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. The core of this platform is powered by several Machine Learning Python Libraries handling everything from data processing, to deep learning model training, and complex optimisation algorithms.

The Libraries team is responsible for designing, developing, and maintaining those Machine Learning Libraries. As a Machine Learning Software Engineer within the team, you will be the crucial link between cutting-edge research and production-ready software. You will collaborate closely with our Research team to translate the latest state-of-the-art models and techniques into robust, easy-to-use, and performant library code. You are a software engineer who thinks like a data scientist, ensuring our libraries are not only robust but also embody the best practices of the machine learning lifecycle.

• Collaborate with product managers and library users to translate functional requirements into robust technical specifications and production-ready code.
• Work closely with our research scientists to productionize novel models and algorithms, integrating them into our core libraries.
• Contribute high-quality, tested, documented, and maintainable code across the library stack, ensuring our core systems are reliable and easy for other engineers to build upon.
• Champion software engineering excellence across the team and company, driving best practices in testing (unit, integration, performance), CI/CD, and system architecture.
• Own your work end-to-end, from ideation and experimentation through to deployment and maintenance in a small, agile team environment.
• Continuously explore and evaluate new techniques and frameworks, helping to guide the technical evolution of our platform.
• Share your knowledge with the team, contribute to our engineering guild, and stay connected with the broader community.

• A passion for the craft of software engineering and building robust, maintainable systems in a collaborative, cross-functional team.
• Solid software engineering skills, with a focus on writing clean, testable, and maintainable code.
• Strong problem-solving skills, with the ability to diagnose complex issues in a high-uncertainty R&D environment.
• A commitment to owning the software development lifecycle, including testing, containerization, and CI/CD.
• A deep understanding of machine learning fundamentals (e.g., model architectures, optimizers, statistical principles) and the data science lifecycle.
• Strong proficiency in Python's scientific computing and Machine Learning ecosystem (e.g., PyTorch, NumPy, SciPy, Pandas).
• An understanding of how high-level Machine Learning frameworks interact with low-level hardware (e.g., C++/CUDA on GPUs).
• A proactive ownership mindset and the ability to navigate ambiguity.
• Excellent collaboration and communication skills, with an ability to discuss complex technical concepts with both researchers and product teams.

• Professional experience with C++ and/or GPGPU programming (e.g., CUDA, Triton) for performance optimization.
• Experience building and maintaining widely-used internal or open-source libraries.
• Experience applying machine learning to scientific domains, particularly with 3D geometric or simulation data.
• Familiarity with model packaging and serialization techniques (e.g., ONNX, TorchScript).

• Equity options – share in our success and growth.
• 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.