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For Companies At a Glance
- Tasks: Scale and optimise multi-cloud GPU clusters while building innovative tools.
- Company: Join a cutting-edge AI company backed by NVIDIA, collaborating with top researchers.
- Benefits: Competitive salary, meaningful equity, full visa sponsorship, and relocation support.
- Other info: Exciting opportunity for career growth in a dynamic startup environment.
- Why this job: Be part of a revolutionary team shaping the future of AI technology.
- Qualifications: Strong systems engineering background with deep Kubernetes and GPU experience.
The predicted salary is between 80000 - 100000 £ per year.
Join a frontier AI company backed by NVIDIA, building large-scale open-weight foundation models alongside researchers and engineers from DeepMind, OpenAI, Meta, Anthropic, and Google Brain.
What You’ll Do
- Scale and optimise multi-cloud GPU clusters
- Build tooling for scheduling, remediation, and node health
- Debug GPU/NCCL performance at cluster scale
- Improve observability, storage, and infrastructure reliability
What They’re Looking For
- Strong systems engineering background
- Deep Kubernetes + GPU infrastructure experience
- Strong coding ability
- Experience with NCCL, distributed systems, and high-performance storage
BONUS: Worked on NVIDIA Blackwell chips (B200, B300, GB200, GB300)
Package
- Salary open to candidate expectations
- Meaningful startup equity
- Full visa sponsorship + relocation support
Software-ontwikkelaar employer: Acceler8 Talent
Contact Detail:
Acceler8 Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software-ontwikkelaar
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving Kubernetes and GPU infrastructure. This is your chance to demonstrate your coding ability and systems engineering background.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of distributed systems and high-performance storage. Practice common coding challenges and be ready to discuss your experience with NCCL and debugging at scale.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Software-ontwikkelaar
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with systems engineering and GPU infrastructure. We want to see how your skills align with what we’re looking for, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about working with cutting-edge AI technology and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Show Off Your Coding Skills: If you’ve got strong coding abilities, let them shine through in your application. Consider including links to any relevant projects or GitHub repositories that demonstrate your expertise, especially in Kubernetes and distributed systems.
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’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Acceler8 Talent
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Kubernetes and GPU infrastructure. Brush up on your coding skills and be ready to discuss your experience with distributed systems and high-performance storage.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in scaling and optimising multi-cloud GPU clusters. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your problem-solving abilities.
✨Demonstrate Your Passion for AI
Since this role is with a frontier AI company, show your enthusiasm for AI technologies. Share any personal projects or research you've done related to AI, and express your eagerness to contribute to large-scale open-weight foundation models.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's projects, culture, and future plans. This not only shows your interest but also helps you gauge if the company aligns with your career goals. For example, ask about their approach to improving observability and infrastructure reliability.