Senior 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>Shape Research group strategy and culture in a significant way, especially in domains of expertise. <ul> <li>Be opinionated and formulate strategy on engineering topics relevant to our Research priorities, especially on: scaled engineering, securing compute, infrastructure stack.</li> <li>Define necessary profiles to execute this strategy.</li> <li>Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment.</li> <li>Nurture younger colleagues to grow their skillset and guide their professional development.</li> </ul> </li> <li>Own Research work-streams at a high-level to deliver outcomes. <ul> <li>Align priorities with problem stakeholders, internal and external.</li> <li>Set the technical direction for the stream and apply judgement and taste to drive progress.</li> <li>Plan roadmaps with clear milestones for key decisions and outcomes.</li> <li>Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap.</li> <li>Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment.</li> </ul> </li> <li>The below activities in particular. <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. <ul> <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> </ul> </li> <li>Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.</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> </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: <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>&nbsp;4 years of experience in a data-driven role in a&nbsp;<em><strong>professional industry</strong></em> setting, where you have been instrumental in most of the below: <ul> <li>scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus); <ul> <li>employing distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);</li> <li>employing 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>building or using C/C++ for computer vision, geometry processing, or scientific computing;</li> <li>following and promoting software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);</li> <li>container-izing and orchestrating compute tasks (Docker, Kubernetes, Slurm);</li> <li>writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.</li> </ul> </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 day