Senior Research Machine Learning Engineer

PhysicsX is hiring a Senior Research Machine Learning Engineer in London, United Kingdom. Level rates it ; you can apply on PhysicsX.

Level's read on this job

Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
The posting mentions visa sponsorship.
The posting mentions PyTorch, TensorFlow and JAX among its tools and skills.
Level classes it as a senior role.
PhysicsX has 39 other open roles on Level.

AI in this role

PyTorchTensorFlowJAX

ml-opscomputer-vision

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.What you'll do

Work closely with our simulation engineers and research scientists to develop an understanding of the physics and engineering challenges we are solving
Work at the intersection of data science and software engineering to transform prototype implementations to robust production-grade model implementations, libraries and tooling
Work with multi-GPU/multi-node distributed systems for training and inference at the scale of PBs of data and hundreds of GPUs
Optimize the models and pipelines on all levels, from job scheduling down to GPU kernels
Design and build scalable and robust infrastructure for end-to-end machine learning applications on cloud (CoreWeave, AWS)
Continuously apply and improve engineering best practices and standards, coach your colleagues in their adoption.

What you'll bring

Enthusiasm about using machine learning for science and engineering, and especially in scaling such solutions to real-world settings
Ability to work autonomously in a fast-paced environment, learn and adapt quickly, scope, plan and deliver effectively
Strong collaboration and communication skills, especially with research scientists
Experience with software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
Experience building ML models and pipelines in Python, using common libraries and frameworks (e.g., PyTorch, TensorFlow, JAX)
Experience with the GPU programming ecosystem, ability to optimise models on all levels of the stack, going down to the level of CUDA/Triton/Warp kernels when necessary
Experience training and serving ML models at scale
Experience with large-scale data processing

Nice to have

Domain knowledge in physics and/or numerical methods, especially CFD
Experience working in the domain of ML for science or engineering
Experience building infrastructure on cloud platforms (e.g., AWS, Azure, GCP, CoreWeave)
Experience with C/C++, especially for computer vision, geometry processing and scientific computing

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

Senior Research Machine Learning Engineer at PhysicsX rates 94 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.

●●●● 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.

Key facts

Senior Research Machine Learning Engineer is an open job at PhysicsX.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in London, United Kingdom.
The job was posted on April 13, 2026.
Seniority: senior.
Applications are handled by PhysicsX. Apply on PhysicsX

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsComputer visionPyTorchTensorFlowJAX

Also common in machine learning engineer jobs at this level

LLM Deep learning Generative AI Spark Kubernetes Fine-tuning

Pay

Typical machine learning engineer job: $198k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used TensorFlow hands-on?
Walk me through how you've used JAX in your day-to-day work.

Adapt your resume

List these exact terms on your resume: ML Ops, Computer vision, PyTorch, TensorFlow, and 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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