At a Glance
- Tasks: Design and optimise HPC & AI performance benchmarks on Google Cloud Platform.
- Company: Join World Wide Technology, a global leader in tech innovation.
- Benefits: Hybrid work model, competitive pay, and a chance to work with cutting-edge technology.
- Other info: 6-month contract with opportunities for career growth and development.
- Why this job: Make an impact in AI/ML while working with advanced accelerator platforms.
- Qualifications: Strong GCP experience and knowledge of HPC concepts required.
The predicted salary is between 50000 - 65000 £ per year.
World Wide Technology (WWT) is a global technology integrator and supply chain solutions provider. Through our culture of innovation, we inspire, build, and deliver business results, from idea to outcome.
World Wide Technology UK is looking for a hands-on Cloud Engineer with strong expertise in HPC and AI/ML performance workloads on Google Cloud Platform (GCP). The role focuses on benchmarking, optimizing, and validating performance across advanced accelerator platforms including NVIDIA GPUs, AMD GPUs, and Google TPUs.
This is a contract role & inside IR35. Contract Duration: 6 months! Location: Manchester, United Kingdom (Hybrid with 2-3 days a week onsite).
Key Responsibilities
- Design and execute HPC & AI performance benchmarks (training, inference, scientific workloads)
- Provision and optimize GPU/TPU-based infrastructure on GCP (A3/A4, TPU pods)
- Analyze performance across frameworks (PyTorch, TensorFlow, JAX, CUDA, ROCm)
- Identify system bottlenecks (compute, memory, network, I/O)
- Build automation tools for benchmarking and reporting
- Collaborate with teams to align workloads with optimal architecture
Required Skills
- Strong experience with GCP (Compute Engine, GKE, Storage, Networking)
- Hands-on with NVIDIA (CUDA/NCCL), AMD (ROCm), and TPUs (XLA/JAX/TF)
- Solid knowledge of HPC concepts (MPI, RDMA, InfiniBand, Slurm/Kubernetes)
- Experience with performance benchmarks (MLPerf, HPL, NCCL, STREAM)
- Proficiency in Python, Bash, and IaC tools (Terraform/Ansible)
- Ability to analyze profiling tools (Nsight, TensorBoard, PyTorch Profiler)
Candidates will be required to go through background checks before commencing the contract. Must be eligible to live and work in the specified work location. Some occasional travel may be required. Only successful candidates will be contacted.
EQUAL OPPORTUNITIES
World Wide Technology is committed to equal opportunities and actively seeks applications from all sectors of the community irrespective of sex, race, colour, nationality, ethnic or national origin, disability, marital status, sexual orientation, having responsibility for dependents, age, religion/beliefs, or any other reason which cannot be shown to be justified.
Cloud Engineer in Manchester employer: WWT EMEA UK LIMITED
World Wide Technology (WWT) is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for Cloud Engineers to thrive. Located in Manchester, the hybrid work model allows for flexibility while providing opportunities for hands-on experience with cutting-edge technologies like GCP, NVIDIA, and AMD. With a strong commitment to employee growth and equal opportunities, WWT empowers its team members to excel in their careers while contributing to impactful projects.
StudySmarter Expert Advice🤫
We think this is how you could land Cloud Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at tech meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GCP, HPC, and AI/ML. It’s a great way to demonstrate what you can do beyond the written application.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to cloud engineering. Get comfortable discussing your experience with NVIDIA GPUs and performance benchmarks—confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who take the initiative. Plus, it helps us keep track of your application better.
We think you need these skills to ace Cloud Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Cloud Engineer role. Highlight your experience with GCP, HPC, and AI/ML workloads. We want to see how your skills match up with what we're looking for!
Showcase Your Projects:Include any relevant projects or benchmarks you've worked on, especially those involving NVIDIA GPUs or Google TPUs. This gives us a clear picture of your hands-on experience and problem-solving skills.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and achievements.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at WWT EMEA UK LIMITED
✨Know Your GCP Inside Out
Make sure you brush up on your Google Cloud Platform knowledge. Be ready to discuss specific services like Compute Engine and GKE, and how you've used them in past projects. Having real examples of how you've optimised GPU/TPU infrastructure will definitely impress.
✨Show Off Your HPC Skills
Since the role focuses on HPC concepts, be prepared to talk about your experience with MPI, RDMA, and InfiniBand. Bring examples of how you've tackled system bottlenecks and what tools you've used for performance benchmarking. This will show that you can hit the ground running.
✨Demonstrate Your Coding Proficiency
You’ll need to showcase your skills in Python and Bash, so be ready to discuss your coding experience. If you’ve built automation tools or worked with IaC tools like Terraform or Ansible, share those stories. Practical examples will help you stand out.
✨Prepare for Technical Questions
Expect technical questions related to AI/ML frameworks like PyTorch and TensorFlow. Brush up on profiling tools such as Nsight and TensorBoard, and be ready to explain how you've used them to analyse performance. This shows you're not just familiar with the tools, but know how to leverage them effectively.
