Research machine learning engineer in London

Research machine learning engineer in London

London Full-Time 63000 - 77000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Collaborate with engineers and scientists to tackle real-world physics challenges using machine learning.
  • Company: Join PhysicsX, a pioneering AI company transforming industrial engineering and manufacturing.
  • Benefits: Enjoy flexible hybrid work, competitive salary, free lunches, and generous parental leave.
  • Other info: Embrace a flat structure where your ideas matter and career growth is supported.
  • Why this job: Make a meaningful impact in AI-driven engineering while working with a talented, diverse team.
  • Qualifications: Passion for machine learning, strong coding skills in Python, and experience with ML frameworks.

The predicted salary is between 63000 - 77000 £ per year.

Описание

Physics X 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.

Physics X is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle.

Задачи

  • 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 (Core Weave, AWS)
  • Continuously apply and improve engineering best practices and standards, coach your colleagues in their adoption

Требования

  • 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., Py Torch, Tensor Flow, 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
  • Будет плюсом: 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, Core Weave); Experience with C/C++, especially for computer vision, geometry processing and scientific computing

Условия

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.

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.

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.

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.

  • 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.
  • Yellow Nest 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.

Research machine learning engineer in London employer: PhysicsX

At PhysicsX, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through access to personal development resources and mentorship opportunities, all while enjoying the benefits of flexible working arrangements in our vibrant Shoreditch office. With equity options and a strong focus on diversity and inclusion, we empower our team to thrive both professionally and personally in a meaningful and rewarding environment.

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Contact Details:

PhysicsX Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research machine learning engineer in London

✨Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at PhysicsX or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

✨Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to PhysicsX.

✨Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like PhysicsX.

✨Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like PhysicsX that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Research machine learning engineer in London

Machine Learning
Data Science
Software Engineering
Python
PyTorch
TensorFlow
JAX

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at PhysicsX.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at PhysicsX and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at PhysicsX

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If PhysicsX uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.