Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Optimise distributed training systems for large-scale multimodal models using thousands of GPUs.
- Company: Leading technology and AI company based in Greater London.
- Benefits: Gain hands-on experience in cutting-edge AI development and enhance your technical skills.
- Why this job: Join a team at the forefront of AI innovation and make a real impact.
- Qualifications: Extensive PyTorch experience and strong understanding of GPU clusters required.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 1500 - 2000 £ per month.
A technology and AI company in Greater London is seeking a Research Intern to optimize distributed training systems for large-scale multimodal models using thousands of GPUs. You will collaborate with the training infrastructure team to build innovative solutions while improving training stability and resource utilization.
Ideal candidates have:
- Extensive PyTorch experience
- A strong understanding of GPU clusters
- Familiarity with advanced parallelization techniques
This role offers a unique opportunity to work at the forefront of AI development.
Multimodal AI Training Infrastructure Engineer employer: lumalabs.ai
Contact Detail:
lumalabs.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Multimodal AI Training Infrastructure Engineer
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and tech space on LinkedIn or at local meetups. We can’t stress enough how valuable personal connections can be in landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving PyTorch and GPU clusters. This gives us a chance to see your work in action and understand your problem-solving approach.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of distributed training systems and parallelization techniques. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Multimodal AI Training Infrastructure Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PyTorch and GPU clusters. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your background makes you a perfect fit for optimising distributed training systems. Let us know what excites you about this opportunity!
Showcase Your Problem-Solving Skills: In your application, mention specific challenges you've faced in previous roles and how you tackled them. We love seeing candidates who can think critically and innovate solutions, especially in the context of training stability and resource utilisation.
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 us you’re keen on joining our team!
How to prepare for a job interview at lumalabs.ai
✨Know Your Tech Inside Out
Make sure you brush up on your PyTorch skills and understand GPU clusters thoroughly. Be ready to discuss your previous experiences with distributed training systems and how you've optimised them in the past.
✨Showcase Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios related to training stability and resource utilisation. Think about how you would approach common challenges in multimodal AI training and be ready to share your thought process.
✨Collaborative Spirit is Key
Since you'll be working closely with the training infrastructure team, highlight any past experiences where teamwork led to successful outcomes. Share examples of how you’ve collaborated on projects and contributed to innovative solutions.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the company’s current projects or future goals in AI development. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
