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- Tasks: Maintain and optimise high-performance computing environments for cutting-edge AI solutions.
- Company: Rapidly growing cloud provider redefining high-performance computing with Nvidia partnerships.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Join a dynamic team and make an impact in the AI and ML ecosystem.
- Qualifications: Experience with HPC systems, Linux, and networking; strong troubleshooting skills.
- Other info: Collaborative environment with excellent career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
A rapidly growing cloud provider is redefining high-performance computing with cutting-edge GPUaaS, delivering scalable, enterprise-grade AI infrastructure at unmatched efficiency. With deep ties to Nvidia, they’re quickly becoming a powerhouse in the US and Europe’s AI and ML ecosystem, providing solutions for HPC, AI, and deep learning workloads.
As the Principal HPC Support Engineer, you will play a pivotal role in maintaining and supporting high-performance computing environments on bare-metal infrastructure, primarily serving clients in research, higher education, and enterprise AI sectors. You will focus on both the software and networking aspects of HPC deployments, ensuring that large-scale GPU clusters remain operational, secure, and optimized for client needs.
Key Responsibilities- System Maintenance and Performance Optimization
- Manage, maintain, and tune bare-metal HPC clusters running Linux-based operating systems (e.g., Fedora, Debian, Ubuntu).
- Optimize Nvidia GPU compute environments, including CUDA, NCCL, and GPU resource management in multi-node HPC clusters.
- Oversee high-speed networking configurations, including InfiniBand (Mellanox), RDMA, and Ethernet fabric tuning for low-latency HPC workloads.
- Configure and fine-tune HPC schedulers (e.g., Slurm, OpenPBS, SGE) for optimal GPU workload distribution.
- Implement containerization strategies (Podman, Docker) and orchestration platforms (K3s, Kubernetes) for managing distributed AI/ML workloads.
- Configure, monitor, and troubleshoot high-performance network fabrics, ensuring low-latency, high-throughput communication between GPU nodes.
- Deploy and maintain InfiniBand, RoCE, and high-speed Ethernet for HPC and AI clusters.
- Collaborate with networking teams to optimize routing, switching, and load balancing for distributed computing environments.
- Work closely with Nvidia engineers and system architects to implement GPUDirect Storage, NVLink, and Magnum IO for accelerated workloads.
- Maintain authentication and authorization systems such as Active Directory, OpenLDAP, and Keycloak.
- Automate system provisioning and configuration using Ansible, Terraform, or other Infrastructure-as-Code tools.
- Monitor system performance using Prometheus, Grafana, and ELK Stack, identifying and resolving bottlenecks in GPU workloads.
- Implement security best practices for multi-tenant HPC clusters, ensuring compliance with industry standards.
- Serve as the lead technical resource for diagnosing and resolving complex software, networking, and hardware issues in large-scale GPU clusters.
- Analyze logs, conduct performance profiling, and debug CUDA, MPI, and RDMA-related issues.
- Work closely with AI/ML research teams, cloud engineers, and enterprise clients to optimize workload performance.
- Support the ongoing development of internal HPC test environments and customer POCs.
- Work cross-functionally with Service Desk, Operations, and Service Delivery Management to ensure seamless service.
- Provide technical documentation, training, and mentorship to junior team members.
HPC Infrastructure and Support Engineer in Plymouth employer: asobbi
Contact Detail:
asobbi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land HPC Infrastructure and Support Engineer in Plymouth
✨Network Like a Pro
Get out there and connect with folks in the HPC and AI community! Attend meetups, webinars, or conferences where you can chat with industry experts. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Don’t just tell potential employers what you can do; show them! Create a portfolio or GitHub repository showcasing your projects related to HPC, GPU optimisation, or networking. This gives you a leg up and demonstrates your hands-on experience.
✨Ace the Interview
Prepare for technical interviews by brushing up on key concepts like CUDA, InfiniBand, and HPC schedulers. Practice common interview questions and consider doing mock interviews with friends or mentors to build confidence.
✨Apply Through Us!
We’ve got your back! Check out our website for the latest job openings in HPC and AI. Applying through us not only gives you access to exclusive roles but also connects you with a supportive community ready to help you land that dream job.
We think you need these skills to ace HPC Infrastructure and Support Engineer in Plymouth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the HPC Infrastructure and Support Engineer role. Highlight your experience with Linux-based systems, GPU environments, and any relevant networking skills. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about high-performance computing and how your skills can contribute to our mission. Keep it engaging and relevant to the job description.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical expertise! Mention specific tools and technologies you’ve worked with, like CUDA, Ansible, or Kubernetes. We love seeing candidates who are hands-on and familiar with the latest in HPC.
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 asobbi
✨Know Your HPC Stuff
Make sure you brush up on your knowledge of high-performance computing, especially around Linux-based systems and Nvidia GPU environments. Be ready to discuss specific tools like CUDA, Slurm, and InfiniBand, as well as any hands-on experience you've had with them.
✨Showcase Your Troubleshooting Skills
Prepare to share examples of how you've diagnosed and resolved complex issues in HPC environments. Think about specific challenges you've faced and how you approached them, especially regarding software, networking, and hardware problems.
✨Demonstrate Collaboration
This role involves working closely with various teams, so be ready to talk about your experience collaborating with others. Highlight any cross-functional projects you've been part of and how you contributed to their success.
✨Ask Smart Questions
At the end of the interview, don’t forget to ask insightful questions about the company's HPC strategies or future projects. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.