Senior HPC Performance Engineer
Senior HPC Performance Engineer

Senior HPC Performance Engineer

Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Analyse performance on multi-GPU clusters and troubleshoot issues for cutting-edge AI applications.
  • Company: Join NVIDIA, a leader in AI and High-Performance Computing innovation.
  • Benefits: Competitive salary, extensive benefits, and a flexible, inclusive work environment.
  • Why this job: Be part of a dynamic team pushing technology boundaries and shaping the future.
  • Qualifications: M.S. or PhD in Computer Science with HPC experience and parallel programming skills.
  • Other info: Opportunities for growth and collaboration across global teams.

The predicted salary is between 36000 - 60000 £ per year.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.Come work for the team that brought to you NCCL, NVSHMEM & GPUDirect. Our GPU communication libraries are crucial for scaling Deep Learning and HPC applications! We## **What you will be doing:*** Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters.* Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack* Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available* Triage and root-cause performance issues reported by our customers* Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information* Collaborate with a very dynamic team across multiple time zones## **What we need to see:**## **Ways to stand out from the crowd:**NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all.* M.S. (or equivalent experience) or PHD in Computer Science, or related field with relevant performance engineering and HPC experience* 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM)* Experience conducting performance benchmarking and triage on large scale HPC clusters* Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)* Implement micro-benchmarks in C/C++, read and modify the code base when required* Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python* Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker)* Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones* Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control* Experience debugging network issues in large scale deployments* Familiarity with CUDA programming and/or GPUs* Experience with Deep Learning Frameworks such PyTorch, TensorFlow #J-18808-Ljbffr

Senior HPC Performance Engineer employer: NVIDIA Corporation

NVIDIA is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration among talented professionals in the fields of Artificial Intelligence and High-Performance Computing. With competitive salaries, comprehensive benefits, and a strong commitment to diversity and inclusion, employees are empowered to grow and thrive while working on cutting-edge technologies that shape the future. Located in a vibrant tech hub, NVIDIA provides unique opportunities for professional development and engagement with a global team dedicated to pushing the boundaries of technology.
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Contact Detail:

NVIDIA Corporation Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior HPC Performance Engineer

✨Tip Number 1

Network, network, network! Reach out to professionals in the HPC and AI fields on platforms like LinkedIn. Join relevant groups and participate in discussions to get your name out there and show your passion for the industry.

✨Tip Number 2

Prepare for technical interviews by brushing up on your parallel programming skills and understanding of performance benchmarking. Practice coding challenges related to C/C++ and Python to showcase your problem-solving abilities during interviews.

✨Tip Number 3

Don’t just apply for jobs; engage with the companies you’re interested in. Follow them on social media, attend their webinars, and comment on their posts. This shows your enthusiasm and can help you stand out from the crowd.

✨Tip Number 4

When you find a role that excites you, apply through our website! Tailor your approach to highlight your experience with HPC clusters and performance analysis, making sure to connect your skills directly to what they’re looking for.

We think you need these skills to ace Senior HPC Performance Engineer

Performance Characterization
Multi-GPU and Multi-Node Clusters
Parallel Programming
Communication Runtime (MPI, NCCL, UCX, NVSHMEM)
Performance Benchmarking
Computer System Architecture
HW-SW Interactions
Operating Systems Principles
Micro-benchmark Implementation in C/C++
Debugging Performance Issues
Scripting Language (Python)
Containers and Cloud Provisioning (Kubernetes, SLURM, Ansible, Docker)
Infiniband/Ethernet Networks
Network Debugging
CUDA Programming
Deep Learning Frameworks (PyTorch, TensorFlow)

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Senior HPC Performance Engineer role. Highlight your experience with parallel programming, performance benchmarking, and any relevant projects that showcase your skills in HPC and GPU technologies.

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about HPC and how your background aligns with our mission at NVIDIA. Don’t forget to mention specific experiences that relate to the job description.

Showcase Your Technical Skills: Be sure to include any technical skills that are relevant to the role, like your proficiency in C/C++, Python, and experience with tools like Kubernetes or Docker. We want to see how you can contribute to our dynamic team!

Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!

How to prepare for a job interview at NVIDIA Corporation

✨Know Your Tech Inside Out

Make sure you brush up on your knowledge of parallel programming and communication runtimes like MPI, NCCL, or NVSHMEM. Be ready to discuss your experience with performance benchmarking and how you've tackled issues in large-scale HPC clusters.

✨Showcase Your Problem-Solving Skills

Prepare to share specific examples of how you've triaged and resolved performance issues in the past. Highlight your ability to debug across the entire hardware/software stack and any tools you've built for performance analysis.

✨Demonstrate Your Collaborative Spirit

Since you'll be working with a dynamic team across multiple time zones, emphasise your adaptability and communication skills. Share experiences where you've successfully collaborated with others, especially in diverse teams.

✨Get Hands-On with the Tools

Familiarise yourself with relevant tools and technologies like Kubernetes, Docker, and Python scripting. If possible, bring along examples of micro-benchmarks you've implemented or any performance data visualisation tools you've developed.

Senior HPC Performance Engineer
NVIDIA Corporation

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