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PhysicsX

Research Scientist - Large Geometry Models

PhysicsX is hiring a Research Scientist - Large Geometry Models in London, United Kingdom. Level rates it ; you can apply on PhysicsX.

Level's read on this job

  • Level rates this research scientist role Builds AI ●●●●: the job is building AI systems.
  • PhysicsX mentions visa sponsorship in this posting.
  • Tools and skills the posting cites include PyTorch, Python and machine learning.
  • Level classifies it as a senior role.
  • Level lists 39 other open roles at PhysicsX.

AI in this role

Conduct advanced AI research focusing on 3D geometry representation, generative models, and physics-informed machine learning.

pytorchpython
machine-learninggenerative-ai3d-geometrydeep-learning

About us

Re-architecting Engineering for the Age of Intelligence

PhysicsX 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.

Note: We are currently recruiting for multiple levels and positions, however please only apply for the role that best aligns with your skillset and career goals.

Geometry is at the heart of how we think about engineering. You will work at the frontier of 3D geometry representation and generation, with a focus on making both of these ready for engineering. You will also work on closing the coupling between geometry and physics, towards generating shapes that are driven by physical objectives.

What you will do 

  • Own a research work-stream: set its technical direction, align priorities with internal and external stakeholders, and apply judgement and taste to drive progress.
  • Design and train generative models over 3D geometry — representations, latent spaces, and the objectives that decide whether generated geometry is physically usable rather than merely plausible.
  • Work against production numerical solvers, so model quality is measured in validated physics rather than proxy metrics.
  • Work with our ML engineers, simulation engineers and customers to turn engineering challenges into mathematical formulations.
  • Champion research directions valuable to the company, nurture more junior colleagues, and publish for both academic and non-academic audiences.

What you bring to the table

  • PhD in CS, ML, mathematics, physics, engineering or a related field, with demonstrated expertise in generative modelling or learned representations of 3D geometry, covering one or more of:
    1. generative models for geometry — VAEs, diffusion and flow matching, autoregressive latent models, scaled to large datasets;
    2. geometric deep learning and 3D vision over point-cloud, mesh, voxel or implicit-field data, including sparse convolution and sparse attention;
    3. neural fields and shape autoencoders.
  • Relevant experience in industry or a research group of comparable intensity, instrumental in: building models and pipelines in PyTorch/CUDA; bespoke problem settings involving geometric or 3D data; iterating on architecture and inductive bias; combining theoretical reasoning with empirical intuition; running experiment pipelines that produce comparable results.
  • Ability to scope and deliver projects, with strong problem-solving skills.
  • Enthusiasm for deep learning and probabilistic methods applied to science and engineering.
  • Publications at premier conferences: SIGGRAPH, SIGGRAPH Asia, CVPR, ICCV, ECCV, NeurIPS, ICML or ICLR, and relevant journals: TOG, TPAMI, JMLR.
  • Desirable: operator learning or probabilistic methods for PDEs; self-supervised pretraining for 3D vision and/or physics surrogacy; generative inverse design linking geometry to physics objectives..

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

Research Scientist - Large Geometry Models at PhysicsX rates 95 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.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningGenerative AI3d GeometryDeep learningPyTorchPython

Also common in research scientist jobs at this level

Pay

Typical research scientist job
$192k

This posting doesn't list pay. Use the typical research scientist figure when pay comes up. See research scientist jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where generative ai was part of your work. What did you do?
  3. Tell me about a project where 3d geometry was part of your work. What did you do?
  4. Tell me about a project where deep learning was part of your work. What did you do?
  5. Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Machine learning, Generative AI, 3d Geometry, Deep learning, and PyTorch. 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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