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- 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 collaborative projects.
- 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: Exciting opportunity for career growth in a dynamic tech environment.
The predicted salary is between 1500 - 3000 £ 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 in London 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 in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech community, especially those who work with multimodal models or GPU clusters. A friendly chat can open doors and give you insights that might just land you that dream role.
✨Tip Number 2
Show off your skills! If you've got projects or contributions related to PyTorch or distributed training systems, make sure to highlight them in conversations. We love seeing practical examples of your expertise in action.
✨Tip Number 3
Prepare for technical interviews by brushing up on advanced parallelization techniques. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your knowledge and problem-solving approach.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always on the lookout for passionate individuals ready to dive into the world of AI development.
We think you need these skills to ace Multimodal AI Training Infrastructure Engineer in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with PyTorch and GPU clusters in your application. We want to see how your skills align with the role, so don’t hold back on showcasing your technical prowess!
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. Mention any relevant projects or experiences that demonstrate your understanding of distributed training systems and parallelization techniques.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see why you’re a great fit for the team.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity in AI development.
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 share specific examples of challenges you've faced in training stability or resource utilisation. Think about how you approached these problems and what innovative solutions you implemented.
✨Familiarise Yourself with Parallelization Techniques
Since this role involves advanced parallelization, it’s crucial to understand various techniques. Be prepared to explain how these methods can improve training efficiency and how you've applied them in real-world scenarios.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects or future goals. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.
