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- Tasks: Build and optimise training infrastructure for cutting-edge robotics models.
- Company: Early-stage robotics and AI company with a focus on innovation.
- Benefits: Competitive salary up to £220k plus equity package.
- Why this job: Join a small, expert team making significant advances in robotics and AI.
- Qualifications: Experience in ML infrastructure and training large-scale models required.
- Other info: Dynamic work environment with opportunities for rapid career growth.
This is an early-stage robotics + foundational AI company building universal robotics foundation models for general-purpose mobile robots. The ambition is to automate the large, under-served parts of the economy that traditional industrial robotics hasn’t touched.
They’re taking a vertical approach: simulation-first data generation, proprietary omni-models, tight hardware integration, and eventually custom silicon. The team is small, technical, and includes people behind some of the most significant advances in robotics and AI in recent years.
You’d be joining the team responsible for the core training stack.
What you'll do:
- Build and optimise training infrastructure for large-scale vision-language and multimodal foundation models used across robotics tasks.
- Design systems for long-context video training, including sequence parallelism at scale.
- Support autoregressive and diffusion-based models for actions and video, including real-time streaming inference.
- Implement sampling during training (self-forcing) to reduce distribution drift.
- Enable RL post-training for multimodal models.
- Own data flow, memory movement, and GPU utilisation across complex training loops.
What you'll need:
- Extensive experience in ML infrastructure, distributed systems, and/or high-performance computing.
- Direct experience training large vision-language or multimodal foundation models.
- Strong background in large-scale distributed training and GPU performance tuning.
- Experience from top AI labs, frontier model teams, or elite infrastructure groups.
Shortlisted candidates will be contacted within 48 hours.
Research Engineer (Robotics - Model Training) in London employer: Axiōma Search
Contact Detail:
Axiōma Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer (Robotics - Model Training) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the robotics and AI space on LinkedIn or at industry events. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to ML infrastructure or multimodal models. We want to see what you can do, so make sure it’s easy for potential employers to find your work.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of training large-scale models and distributed systems. We recommend doing mock interviews with friends or using online platforms to get comfortable with the questions you might face.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals like you. By applying directly, you’ll ensure your application gets the attention it deserves, and who knows, you might just be the perfect fit for our team!
We think you need these skills to ace Research Engineer (Robotics - Model Training) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Research Engineer role. Highlight your experience in ML infrastructure and any projects related to robotics or AI. We want to see how your skills align with what we’re doing!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for robotics and AI, and explain why you’re excited about joining our team. Let us know how your background makes you a perfect fit for this role.
Showcase Relevant Projects: If you've worked on any relevant projects, make sure to include them in your application. We love seeing practical examples of your work, especially if they involve large-scale training or multimodal models!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures it gets into the right hands. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Axiōma Search
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning infrastructure and distributed systems. Be ready to discuss your experience with large-scale vision-language models and how you've optimised GPU performance in the past.
✨Showcase Your Projects
Prepare to talk about specific projects you've worked on that relate to training multimodal foundation models. Highlight any challenges you faced and how you overcame them, especially in areas like real-time streaming inference or data flow management.
✨Ask Smart Questions
Think of insightful questions to ask during the interview. This could be about their approach to simulation-first data generation or how they integrate hardware with their training stack. It shows you're genuinely interested and have done your homework.
✨Be Ready for Technical Challenges
Expect some technical questions or even a coding challenge related to your expertise. Practise explaining your thought process clearly, as communication is key when discussing complex topics like RL post-training or sequence parallelism.