Senior Research Scientist | Model Scaling

ABOUT US 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. NOTE: 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. WHAT YOU WILL DO  * Shape Research group strategy and culture in a significant way, especially in domains of expertise. * Be opinionated and formulate strategy on engineering topics relevant to our Research priorities, especially on: scaled engineering, securing compute, infrastructure stack. * Define necessary profiles to execute this strategy. * Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment. * Nurture younger colleagues to grow their skillset and guide their professional development. * Own Research work-streams at a high-level to deliver outcomes. * Align priorities with problem stakeholders, internal and external. * Set the technical direction for the stream and apply judgement and taste to drive progress. * Plan roadmaps with clear milestones for key decisions and outcomes. * Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap. * Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment. * The below activities in particular. * 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. * 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. * 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. * Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success. * Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems. * 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.   WHAT YOU BRING TO THE TABLE * 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. * Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. * Excellent collaboration and communication skills — with teams and customers alike. * 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. *  4 years of experience in a data-driven role in a professional industry setting, where you have been instrumental in most of the below: * * scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus); * employing distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton); * employing cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP); * 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; * building or using C/C++ for computer vision, geometry processing, or scientific computing; * following and promoting software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps); * container-izing and orchestrating compute tasks (Docker, Kubernetes, Slurm); * writing pipelines and experiment environments, including running experiments in pipelines in a systematic way. WHAT WE OFFER Build what actually matters 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. Learn alongside exceptional people 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. Influence over hierarchy We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected. Sustainable pace, long-term ambition 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. And it doesn’t stop there … 🚀 Equity options - share meaningfully in the company you’re helping to build. 🏦 10% employer pension contribution - because investing in future matters. 🍽️ Free office lunches - to keep you energised and focused. 👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most. 🍼 YellowNest nursery scheme - to help working parents manage childcare costs. ☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters. 🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind. 💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing. 👀 Eye tests - because good work depends on good health. 📈 Personal development - dedicated support for learning, development, and leveling up over time. 💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it. 🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener. 🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric. 🔎 Watch this space, we’re continuing to build this as we grow…   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.    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. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery.  Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you.    ABOUT ISO Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.   RESEARCH ENGINEERING (MACHINE LEARNING), LONDON  We are looking for Research Engineers with different levels of experience - Mid through to Senior, Staff, Principal or equivalent levels. YOUR IMPACT  This is an exciting opportunity for you to contribute to frontier research at the intersection of AI and drug design. Working in a highly creative, iterative environment, you will be partnering with scientists and engineers to advance foundational models that will transform the biopharmaceutical world as we know it.   You will draw upon your existing engineering and Machine Learning experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems. WHAT YOU WILL DO  Implementation & Optimisation: * Translate research concepts into practical implementations by developing and optimising state-of-the-art AI models, and building and maintaining robust codebases, data pipelines, and infrastructure for training and evaluation. Experimentation & Evaluation: * Design, implement, and run experiments to evaluate the performance and robustness of ML models, using a full spectrum of state-of-the-art machine learning methods. Evaluating, tuning, and maintaining AI/ML models (which includes collecting and preparing data as needed) Evaluation & Inference: * Implement algorithms and software to analyse and evaluate the performance of AI models. * Optimising performance of AI/ML models such as Diffusion models, Transformers, GNNs, leveraging a deep understanding of the AI/ML hardware+software stack * Advise on how to bring AI/ML models to production and/or integrating them into product offerings, and monitoring and refining their behavior. * Developing specialised tools/frameworks/infrastructure to aid in the work above Collaboration & Knowledge Sharing: * Work closely with research scientists and engineers, contributing to team discussions, sharing knowledge, and actively participating in code reviews to foster a collaborative environment. Innovation & Impact: * Proactively identify and address technical challenges, stay updated on the latest AI advancements, and focus on developing solutions that enable scaling our wider foundation and applied model platforms. * Ability to execute on independent engineering projects and software development towards research goals. SKILLS AND QUALIFICATIONS ESSENTIAL * Academic Background: Advanced degree (Master’s or PhD) in a highly quantitative field (Computer Science, AI, Physics, Mathematics, etc.) or equivalent practical experience. * ML Fundamentals: Deep understanding of machine learning principles and techniques. * Framework Expertise: Strong proficiency in deep learning frameworks such as JAX or PyTorch. * Modern Architectures: Hands-on experience building and working with modern model architectures (e.g., Transformers, GNNs, Diffusion Models). * Full ML Lifecycle: Experience taking models from conception to production (scoping, data analysis, training, debugging, evaluation, benchmarking, and deployment). * Engineering Excellence: Excellent software development skills with strong algorithms and data structures fundamentals. * Collaboration & Communication: An excellent team player with strong written and verbal communication skills, able to collaborate seamlessly in a cross-disciplinary environment. * Agency: Self-directed with an ability to navigate ambiguity, propose and own complex projects, learn the necessary context, and readily adapt to new domains and developments. Nice to have * Proven Research Record: A history of scientific contributions (e.g., publications at NeurIPS, ICML, ICLR, CVPR) or significant contributions to state-of-the-art AI models. * Scale & Performance: Experience training models across distributed systems (multi-GPU/multi-node) and optimising training and inference performance (e.g., XLA, Triton, CUDA, Pallas). * Domain Knowledge: A strong interest in, or knowledge of, biochemistry, computational biology, or drug discovery fundamentals. * Industry Experience: Proven track record working in reputable tech companies or research labs. * Applied ML: Experience developing models developed for real-world applications. * Infrastructure: Solid technical infrastructure knowledge and experience with low-level engineering (e.g., GCP, Kubernetes, Docker) CULTURE AND VALUES We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it.  Thoughtful Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day. Brave Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less. Determined Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we. Together Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere. CREATING AN EXTRAORDINARY COMPANY We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. HYBRID WORKING It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call. Please note that when you submit an application, your data will be processed in line with our privacy policy. >> Click to view other open roles at Isomorphic Labs