At a Glance
- Tasks: Lead the design of cutting-edge AI systems for advanced materials in data centres.
- Company: Join Orbital Industries, a global leader in deep tech and engineering innovation.
- Benefits: Competitive salary, diverse team, and opportunities for professional growth.
- Why this job: Make a real impact by bridging AI and industry to solve global technology challenges.
- Qualifications: 5+ years in ML/AI engineering with leadership experience; passion for craftsmanship and learning.
- Other info: Dynamic environment fostering curiosity and collaboration across multiple locations.
The predicted salary is between 54000 - 84000 £ per year.
Orbital's hardware solutions solve the biggest challenges in data centers. Each of our products contains an advanced material discovered with our AI, giving it breakthrough real-world performance. We are looking for ambitious thinkers and builders; those excited by the challenge of bridging AI and industry, chemistry and computation, discovery and deployment.
Our mission is to usher in an era where new, advanced materials are both discovered and engineered with AI and we will use this to build hardware that solves major global technology challenges. Joining Orbital Industries means working at the intersection of deep tech, applied science, and engineering innovation. We are a truly global organisation with sites in London (UK), San Francisco (CA), Princeton (NJ) & Calgary (Canada) building teams in ML Research and Product Development to Mechanical and Chemical Engineering, offering opportunities for talented individuals who want to shape the future of materials and their applications in high-impact industries.
As a Staff Machine Learning Researcher at Orbital, you will architect cutting edge AI systems for the multi-scale design of physical technologies. When we say multi-scale, we mean it: we build world-class foundation models for simulating both the microscopic motion of atoms and the macroscopic flow of liquids in 1GW data centers. We then co-design across these different scales using the ingenuity of our scientists and engineers, augmented with best-in-class domain agents.
Building cutting edge AI systems requires a world-class team and leadership. In this role you will provide that leadership, setting exceptionally high engineering standards and driving projects from prototype through to production deployment. In addition to technical leadership, this role requires people management; you will be dedicated to mentoring and fostering the growth of your team.
First and foremost, we want to work with someone with a love of craftsmanship, continual learning, and building systems that scale. We also value low ego, and a genuine passion for using AI to solve major global industrial technology challenges.
Key Responsibilities- Set the technical bar and ensure engineering excellence
- Establish and maintain exceptionally high standards for code quality, system architecture and ML engineering practices through hands-on coding and technical review
- Create a culture of technical rigour, first-principles thinking and engineering craftsmanship
- Design robust, well-engineered systems that others can build upon, balancing research velocity with production requirements
- Drive technical decisions on model selection, training approaches and deployment strategies
- Lead and deliver high-impact AI projects across diverse domains
- Develop and deploy AI solutions across the entire technology development pipeline—computational chemistry simulations, agentic workflows and beyond
- Rapidly upskill in new technical areas through close collaboration with domain experts (no prior chemistry or materials experience required)
- Demonstrate strong implementation skills through hands-on development, contributing significantly to the codebase
- Balance research rigour with pragmatic engineering to deliver production-ready systems at scale
- Mentor, develop and lead technical talent
- Provide technical leadership, mentorship and career development for AI engineers
- Manage the intake and development of AI residency programme participants
- Foster a culture of learning, curiosity and first-principles problem solving
- Build a high-performing team that can independently tackle complex, novel problems
- 5+ years of professional experience in ML/AI engineering, with at least 2 years in technical leadership or management roles
- Proven experience training, evaluating and productionising AI models at scale, with deep understanding of the full ML lifecycle from research to deployment
- Strong engineering fundamentals with the ability to write high-quality, maintainable code and architect robust systems
- Experience managing, mentoring or leading technical teams, with a commitment to developing others' skills and careers
- A strong ability to reason about algorithms, system design and ML engineering trade-offs
- A genuine interest in building AI systems that enable breakthrough scientific and industrial applications
Upon reading Hamming's You and Your Research, you resonate with quotes such as:
- "Yes, I would like to do first-class work"
- "You should do your job in such a fashion that others can build on top of it, so they will indeed say, 'Yes, I've stood on so and so's shoulders and I saw further.'"
- "Instead of attacking isolated problems, I made the resolution that I would never again solve an isolated problem except as characteristic of a class"
- Experience with physics-informed or chemistry-focused AI applications.
- Experience building or fine-tuning large language models.
- Experience with agent-based systems, tool use or agentic workflows.
- Contributions to open-source ML projects or published research.
Orbital Industries is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Staff Machine Learning Researcher in London employer: Orbital
Contact Detail:
Orbital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Researcher in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Orbital. Use LinkedIn or even Twitter to connect with current employees and ask about their experiences. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! If you’ve got projects or research that align with what Orbital is doing, don’t be shy. Create a portfolio or GitHub repository showcasing your work in ML/AI. This gives you a chance to demonstrate your craftsmanship and passion for building systems that scale.
✨Tip Number 3
Prepare for the interview like it’s the championship game! Research Orbital’s products and think about how your experience can contribute to their mission. Be ready to discuss your technical leadership style and how you foster growth in your team – they want to see your mentoring side!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Orbital team. Don’t forget to follow up after applying; a little nudge can go a long way!
We think you need these skills to ace Staff Machine Learning Researcher in London
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and its potential to solve real-world problems shine through. We love candidates who are genuinely excited about bridging the gap between technology and industry!
Highlight Your Leadership Skills: Since this role involves technical leadership, make sure to showcase your experience in mentoring and developing teams. Share specific examples of how you've guided others and fostered a culture of learning.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your experiences and skills, making it easy for us to see how you fit into our mission at Orbital.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Orbital
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals and the latest advancements in AI. Orbital is looking for someone who can bridge the gap between AI and industry, so be prepared to discuss how your experience aligns with their mission of using AI to solve global technology challenges.
✨Show Your Leadership Skills
Since this role involves technical leadership and mentoring, think of examples from your past where you've successfully led a team or project. Be ready to share how you fostered growth in others and maintained high engineering standards, as this will resonate well with what Orbital values.
✨Demonstrate Problem-Solving Mindset
Orbital is all about tackling complex problems, so come prepared with examples of how you've approached challenging projects. Discuss your thought process, the first-principles thinking you applied, and how you balanced research with practical engineering solutions.
✨Cultural Fit Matters
Orbital values low ego and a genuine passion for craftsmanship. During the interview, express your enthusiasm for continuous learning and collaboration. Share how you’ve contributed to a positive team culture in the past, as they’re looking for someone who can build a high-performing team.