Simulation Engineer (CFD) - Large Physics Models
PhysicsX is hiring a Simulation Engineer (CFD) - Large Physics Models in London, United Kingdom. Level rates it ; you can apply on PhysicsX.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- PhysicsX mentions visa sponsorship in this posting.
- Tools and skills the posting cites include JAX.
- Level lists 38 other open roles at PhysicsX.
- The role was posted in the last few days.
AI in this role
About us
Re-architecting Engineering for the Age of IntelligencePhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
About the role
Large Physics Models need data, and the quality, diversity and cost of that data shape is what we need to define. As a Simulation Engineer in our Research team, you will build the simulation side of that foundation. You’ll work in a research environment, alongside ML researchers and engineers, on how physics-based simulation and machine learning can be combined in ways that haven’t been done before.
You’ll be working at the frontier of Large Physics Model development, shaping new AI paradigms for our customers to benefit from in the future. You will aid in data generation, how, and at what fidelity, so that the models we build are both accurate and affordable to train.
What you will do
- Generate simulation data for training large-scale ML models, drawing on a mix of methods and fidelity levels.
- Develop and implement solvers and numerical methods, potentially in modern differentiable or GPU-native frameworks such as JAX or NVIDIA Warp.
- Work with multi-fidelity data: understand tradeoff between fidelity and CFD simulators and how the two can be combined.
- Use commercial and open-source CFD tools to produce reference data
- Collaborate closely with ML researchers and engineers, translating between the physics and the models, and helping the team get the best corpus possible.
- Contribute to the technical direction of our data generation work and flag the simulation investments that will unlock research progress.
What you bring
- A postgraduate degree (MSc or PhD) in engineering, applied mathematics, physics or a related field, ideally with research involving numerical analysis of PDEs or computational engineering. A PhD is preferred but not required.
- At least 1-2 years of industry experience in CFD, ideally in turbomachinery, aerospace, defence or the chemical and process industries (CPI).
- Experience developing numerical solvers or PDE solvers, for example in JAX, Warp or a comparable framework.
- Hands-on experience with at least one commercial CFD solver, such as Simcenter STAR-CCM+ or Ansys Fluent.
- Comfort working in a research setting, where problems are open-ended and the path isn’t always clear.
Strongly preferred
- Practical experience with OpenFOAM.
- Exposure to ML or surrogate model development, or experience working directly with ML teams.
Why join us
- Work at the frontier of Large Physics Models, in a team where simulation expertise shapes the research direction.
- Join a research environment with real access to ML talent and compute.
- Influence how we think about data, fidelity and physics in AI.
Please note, this role is based in London, working 2-3 days per week in our central office.
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 employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.How we rate this
Simulation Engineer (CFD) - Large Physics Models at PhysicsX rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
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Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used JAX hands-on?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: JAX. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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