Machine Learning Software Engineer, Research

<div class="content-intro"><h2>About us</h2> <div>PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.</div> <div>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 &amp; Defense, Materials, Energy, Semiconductors, and Automotive.</div></div><h3><strong>Note:&nbsp;</strong>We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.</h3> <h2><strong>What you will do&nbsp;</strong></h2> <ul> <li>Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.</li> <li>Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.</li> <li>Transform prototype model implementations to robust and optimised implementations.</li> <li>Implement distributed training architectures (e.g., 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.</li> <li>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.</li> <li>Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.</li> <li>Own Research work-streams at different levels, depending on seniority.</li> <li>Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.</li> <li>Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.</li> <li>Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.</li> </ul> <h2><strong>What you bring to the table</strong></h2> <ul> <li>Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.</li> <li>Ability to work autonomously and scope and effectively deliver projects across a variety of domains.</li> <li>Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.</li> <li>Excellent collaboration and communication skills — with teams and customers alike.</li> <li>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:<br> <ul> <li>Scientific computing;</li> <li>High-performance computing (CPU / GPU clusters);</li> <li>Parallelised / distributed training for large / foundation models.</li> </ul> </li> <li>Ideally &gt;2 years of experience in a data-driven role <em><strong>in a professional setting</strong></em>, with exposure to: <ul> <li>scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);</li> <li>distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);</li> <li>cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP);</li> <li>building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;</li> <li>C/C++ for computer vision, geometry processing, or scientific computing;</li> <li>software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);</li> <li>container-ization and orchestration (Docker, Kubernetes, Slurm);</li> <li>writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.</li> </ul> </li> </ul> <h2><strong>What we offer</strong></h2> <p><strong>Build what actually matters</strong></p> <p>Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.</p> <p><strong>Learn alongside exceptional people</strong></p> <p>Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.</p> <p><strong>Influence over hierarchy</strong></p> <p>We operate with a flat structure: good ideas win&nbsp;- wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.</p> <p><strong>Sustainable pace, long-term ambition</strong></p> <p>Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.</p> <p><strong>And it doesn’t stop there …</strong></p> <p>🚀&nbsp;<strong>Equity options</strong>&nbsp;- share meaningfully in the company you’re helping to build.</p> <p>🏦&nbsp;<strong>10% employer pension contribution</strong>&nbsp;- because investing in future matters.</p> <p>🍽️&nbsp;<strong>Free office lunches</strong>&nbsp;- to keep you energised and focused.</p> <p>👶&nbsp;<strong>Enhanced parental leave</strong>&nbsp;- 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.</p> <p>🍼&nbsp;<strong>YellowNest nursery scheme</strong>&nbsp;- to help working parents manage childcare costs.</p> <p><strong>☀️&nbsp;25 days of Annual Leave (+ Public Holidays)</strong><span class="Apple-converted-space">&nbsp;</span>- because taking time to rest matters.</p> <p>🏥&nbsp;<strong>Private medical insurance</strong>&nbsp;- 100% employee cover, giving you complete peace of mind.</p> <p>💪&nbsp;<strong>Wellhub Subscription</strong><span class="Apple-converted-space">&nbsp;</span>- gain access to