Senior HPC Applications Engineer at NVIDIA

Westford, Massachusetts, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

High-Performance Computing, Quantum ComputingIndustries

Requirements

12+ years of experience in HPC application performance engineering, computational science, or scientific software development
Strong background in GPU programming (CUDA, cuQuantum, CUDA-Q) and parallel programming (MPI, OpenMP)
Proficiency with Linux, Slurm, containerization, and CI/CD pipelines (GitHub, Jenkins, Ansible, or GitLab CI)
Experience in profiling, benchmarking, monitoring, and optimizing scientific or AI/ML applications on multi-GPU systems
Working knowledge of NVIDIA HPC SDK, CUDA-Q, or cuQuantum stack
Bachelor’s or Master’s degree (or equivalent experience) in Computer Science, Physics, Applied Mathematics, or Engineering (PhD a plus)
Excellent communication and collaboration skills to support a multidisciplinary research community

Responsibilities

Collaborate with quantum and domain scientists to install, configure, compile, and optimize research applications on the HPC + quantum environment
Profile and tune performance for GPU-accelerated and hybrid workloads using tools such as NVIDIA Nsight, nvprof, and CUDA-Q profilers
Optimize job execution and resource utilization via Slurm policies, GPU partitioning, and hybrid orchestration between classical and quantum nodes
Develop and maintain containerized environments (Singularity, Kubernetes, or Docker) to ensure reproducible builds and easy deployment
Advise researchers on parallelization strategies, CUDA kernels, MPI configurations, and scaling behaviors
Work with system engineers to validate firmware, driver, and library configurations that maximize application performance (e.g., CUDA, cuQuantum, cuBLAS, NCCL)
Integrate quantum SDKs and simulators (e.g., CUDA-Q, Qiskit, or IonQ/QuEra APIs) into HPC workflows
Establish performance baselines and benchmarking suites for GPU and hybrid workloads; publish metrics and dashboards
Support and train users — from onboarding and code migration to advanced performance debugging. Customer first focus
Contribute to architecture evolution by providing feedback on workload patterns, bottlenecks, and future capacity planning

Skills

HPC

GPU

CUDA

Nsight

nvprof

CUDA-Q

Slurm

Singularity

Kubernetes

Docker

MPI

cuQuantum

cuBLAS

NCCL

Qiskit

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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