HPC & AI Performance Engineer

HPC & AI Performance Engineer

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work.

We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.

Our culture thrives on finding new and better ways to accelerate what's next.

We know varied backgrounds are valued and succeed here.

We have the flexibility to manage our work and personal needs.

We make bold moves, together, and are a force for good.

If you are looking to stretch and grow your career our culture will embrace you.

Open up opportunities with HPE.

Job Description:

HPE operates at the forefront of a fast-moving HPC and AI industry.

We are looking for driven engineers who thrive on complex technical challenges and consistently deliver high-quality results that strengthen the performance, competitiveness, and success of HPE's HPC & AI solutions for customers worldwide.

This position will support government accounts.

Therefore, due to federal export-control regulations, the selected candidate must hold U.S.

citizenship , U.S.

lawful permanent resident/Green Card status or otherwise have a category of refugee/asylee status enabling them to perform the role without requiring a license under the International Traffic in Arms Regulations (ITAR) or Export Administration Regulations (EAR).

Required Responsibilities:



* Lead HPC and AI benchmarking projects across CPU, GPU, network, memory, and storage platforms.


* Evaluate HPE and competitive HPC and AI architectures using performance models and benchmark data.


* Run and analyze scientific, engineering, large language model (LLM), AI training and inference, storage, and I/O workloads.


* Identify performance bottlenecks and optimize applications, AI frameworks, libraries, compilers, runtimes, and system software.



* Apply parallel computing, GPU acceleration, profiling, and memory and I/O optimization to deliver credible, repeatable results.

Required Qualifications:



* 6+ years of Experience with HPC and AI workloads, including scientific and engineering applications, MLPerf, large language models such as DeepSeek, Kimi K2.6 or K3, and gpt-oss-120b, AI training and inference, storage benchmarks, and performance-profiling tools.

Relevant coursework and internship experience will be considered.


* Knowledge of HPC and AI system architecture, including CPUs, GPUs and other accelerators, memory, networking, storage, and software stacks, with the ability to explain their impact on application and benchmark performance.


* Understanding of parallel and distributed programming techniques, including MPI, OpenMP, OpenSHMEM, algorithms, and performance considerations for...