
PhysicsX · Singapore
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 softwar...
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.
You are a problem solver and builder, passionate about creating practical solutions that help customers make better engineering
decisions. You can grasp and apply advanced engineering concepts across multiple industries, and you excel at working directly
with internal and external stakeholders, often on-site, to develop high-fidelity simulation models that feed into AI tools that
are both useful and used.
You bring deep expertise in fluid mechanics, heat transfer, and multiphase modelling within bioprocess and chemical engineering
environments. You are highly proficient in at least one of Star-CCM+, OpenFOAM, or Fluent, and experienced modelling the complex
flow behaviour that arises in industrial bioprocess systems. You are adept at automating these tools to create scalable
optimisation workflows. Experience in parametric CAD modelling (NX or CATIA) and coding in Python (or the ability to pick up new
programming languages quickly) is an advantage.
With 5–7 years of industry experience (post-MEng, MSc, or PhD) in a commercial environment, you are ready to hit the ground
running. You are confident setting up simulations independently, interpreting complex results with rigour, and making sound
decisions grounded in solid engineering judgement.
including custom solver and boundary condition development.
industrial and process engineering applications.
regimes
(e.g. biokinetic, combustion, or electrochemical frameworks)
spargers, and free-surface interfaces
design optimisation and DoE studies
integration for model validation
against physical measurements
transient simulations on cloud (Flux) and on-premise resources
design space exploration and process optimisation
optimisation workflows; applying data sampling techniques (LHS, quasi-random, adaptive) to efficiently cover design space
systematically improving model fidelity
communicating results clearly, recommending actionable next steps, and balancing accuracy with efficiency under commercial
deadlines
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.
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.
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. WHO WE'RE LOOKING FOR As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used. You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 5 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers. THIS ROLE As a Principal MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes. You'll: * Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments. * Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence. * Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars. * Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others. * Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure. * Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site. * Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX. As a senior member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader. OUR DELIVERY TEAMS DRIVE INNOVATION TO TURN AI MODELS INTO PRACTICAL SOLUTIONS - READ OUR BLOG TO LEARN MORE ABOUT HOW YOU’LL CONTRIBUTE TO THIS EXCITING JOURNEY! 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.
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. WHO WE'RE LOOKING FOR As a Principal Data Scientist (Algorithm Engineer) in Delivery, you are an experienced problem solver and technical leader who is passionate about building practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embeds cutting edge AI models into tools that are useful and used. You've consistently tackled difficult problems that require strong foundations in data driven modelling and deep learning techniques, with extensive hands-on experience in probabilistic methods and predictive modelling. Your expertise in python, along with advanced proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with proven ability to architect and deploy scalable, production-ready models and data pipelines. With industry experience (post Masters of PhD) in a commercial, you're ready to not only execute but also lead and mentor others. You're truly excited about growing both your technical expertise and leadership skills, naturally taking ownership of complex data science work streams and guiding teams to success. You continuously improve the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers. THIS ROLE In this role, you'll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving, while providing technical leadership to your team. You'll build the foundations for successful, impactful solutions by: * Leading pre-processing and analysis of complex data to prepare it for use in predictive modelling, establishing best practices and methodologies for your team. * Architecting and developing innovative deep learning models in combination with state-of-the-art optimisation methods to predict and control the behaviour of physical systems. * Taking full responsibility for the quality, accuracy and impact of your work and the work of your team. * Designing, building, and testing data pipelines that are reliable, scalable, and robustlyeasily deployable in production environments. * Leading cross-functional collaboration with simulation engineers to ensure seamless integration of data science models with simulations. * Driving internal R&D and product development, helping to refine models and identify new areas of application. * Mentoring junior team members and providing technical guidance to help them grow. * Leading open communication and presentations with both technical teams and customers, helping onboard users and co-develop with customers. * Representing PhysicsX as a technical authority when traveling to customer sites in North America, Europe, Asia, Oceania, an average of 2-3 weeks per quarter, where you'll collaborate closely with customers to build solutions on site. As a senior member of the team, you'll have significant influence on our technical direction and the opportunity to shape future solutions and products, while developing your skills as a technical leader. OUR DELIVERY TEAMS DRIVE INNOVATION TO TURN AI MODELS INTO PRACTICAL SOLUTIONS - READ OUR BLOG TO LEARN MORE ABOUT HOW YOU’LL CONTRIBUTE TO THIS EXCITING JOURNEY! 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.
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, HOWEVER PLEASE ONLY APPLY FOR THE ROLE THAT BEST ALIGNS WITH YOUR SKILLSET AND CAREER GOALS. THE ROLE The Principal ML Infrastructure Engineer will extend and operate the infrastructure that powers our research model training, fine-tuning, and serving pipelines. You will be embedded within our Research function, partnering directly with ML engineers and research scientists to ensure they can train Large Physics Models efficiently and reliably at scale. TEAM CONTEXT In this role, you will be vertically embedded in Research, working daily with: * Research Scientists who determine the model architectures and methods * ML Engineers who implement and develop the models * Simulation Data Engineers who are accountable for upstream data pipelines You will have end-to-end responsibilities over the research infrastructure, with the autonomy to make architectural decisions and the responsibility to keep data flowing reliably. Horizontally, you will be part of an infrastructure engineering group responsible for infrastructure across the company. WHAT YOU WILL DO TRAINING INFRASTRUCTURE * Design and operate distributed training infrastructure for neural operator architectures (Transolver, Point Cloud Transformer, etc.) on our large NVIDIA DGX B200 platform. * Optimize training pipelines for throughput, fault tolerance, and cost efficiency, including checkpointing strategies, gradient accumulation, and multi-node synchronization. * Build and maintain experiment tracking and observability systems that give researchers clear visibility into training runs, hyperparameter sweeps, and model performance. DATA I/O AND PERFORMANCE * Solve data loading bottlenecks for large-scale mesh datasets. * Optimize data pipelines for efficient I/O from cloud storage, including prefetching, caching, and format optimization. * Work with heterogeneous data sources of varying formats and resolutions. MODEL SERVING AND DEPLOYMENT * Build serving infrastructure for pre-trained LPMs, supporting both zero-shot inference and uncertainty quantification (Monte Carlo Dropout). * Design and implement model packaging pipelines for customer deployment. Models must run reliably in customer environments with fine-tuning capabilities. * Ensure reproducibility: any model checkpoint should be deployable with consistent behaviour. PLATFORM AND TOOLING * Improve developer experience for the Research team with fast iteration cycles, reliable CI/CD, clear debugging tools. * Collaborate with the broader Infrastructure team on shared patterns and standards. WHAT YOU BRING TO THE TABLE * Ability to scope and effectively deliver projects, prioritising activity as needed. * Problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. * Excellent collaboration and communication skills, especially in a research setting. You can translate "the model isn't converging" into infrastructure hypotheses and solutions, and can bridge technical abstractions with implementations. * 5+ years of experience building and operating ML infrastructure at scale: * Deep expertise in distributed training: you've debugged NCCL hangs, optimized collective communication, and know when to use FSDP vs. DDP vs. pipeline parallelism * Strong systems fundamentals: Linux, networking (including domain specific NVLink and InfiniBand), storage I/O, profiling and performance optimization * Production experience with Kubernetes and SLURM for job orchestration on GPU clusters * Proficiency in Python and ML frameworks (PyTorch strongly preferred) * Experience with cloud GPU infrastructure; ideally CoreWeave or similar GPU/HPC-focused clouds IDEALLY * Experience with geometric deep learning or neural operators, ****architectures that operate on meshes, point clouds, or graphs * Background in HPC for simulation engineering, familiarity with how CFD/FEA workflows generate and consume data * Experience building model serving infrastructure with latency and throughput requirements * Familiarity with experiment tracking tools (Weights & Biases, MLflow) and observability stacks (Prometheus, Grafana) * Experience packaging models for deployment into customer environments (containers, model registries, versioning) 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.