Senior HPC and Quantum Systems Engineer

NVIDIA•Westford, MA

1d•Hybrid

About The Position

NVIDIA is seeking a Senior HPC & Quantum Systems Engineer to help architect, deploy, and operate a first-of-its-kind Accelerated Quantum Computing Center in the Boston area. This role sits at the intersection of data center infrastructure, high-performance computing, and emerging quantum systems, and will be essential to turning experimental quantum hardware into a reliable, high-impact research platform. You will lead all aspects of the day-to-day technical ownership of a tightly coupled GPU supercomputing environment coordinated with multiple quantum modalities. This is not a pure research role nor a traditional HPC admin role—it is a systems engineering position dedicated to exploring quantum computing integration with classical systems. This role is ideal for someone who has built and operated production HPC environments, understands low-level systems and networking, and is excited to work hands-on with quantum hardware as it transitions from lab prototypes to operational infrastructure. This position plays a central role in bridging quantum research and operational computing infrastructure. You will directly influence how quantum systems are coordinated, scaled, and made usable by researchers, crafting both internal capabilities and external partnerships. Your work will help transform quantum computing from experimental hardware into a dependable, accelerated computing resource. It will operate alongside one of the most advanced GPU platforms in the world! This will materially impact the future of scientific computing.

Requirements

12+ years of hands-on experience operating HPC or large-scale compute infrastructure in production environments.
Bachelor’s degree or Master’s degree with equivalent experience in Physics, Electrical/Computer Engineering, Computer Science (PhD a plus).
Strong background in Linux systems administration, job schedulers (Slurm or equivalent), and computing environments committed to reliable operation.
Proven experience working in data center environments, including networking, storage, power, and operational constraints.
Familiarity with quantum computing concepts and hardware architectures (neutral atom, trapped ion, superconducting, photonic).
Experience with or strong interest in quantum software environments including CUDA-Q, Qiskit, Cirq, PennyLane, Braket, or similar.
Comfort working across system boundaries: control systems, APIs, networking, and performance tooling.

Nice To Haves

Direct experience integrating or hosting physical quantum hardware in a data center or HPC environment.
Deep knowledge of quantum–classical orchestration, low-latency data paths, scientific application support, and/or real-time control considerations.
Experience working with NVIDIA tools and frameworks.
Experience bridging experimental research teams and production infrastructure.

Responsibilities

Build, deploy, and operate a hybrid computing platform combining large-scale NVIDIA GPU clusters with physical quantum processors (neutral atom, trapped ion, superconducting, and future modalities).
Integrate quantum control systems and access nodes with HPC infrastructure using APIs, scientific applications, and orchestration frameworks such as CUDA-Q, cuQuantum, NVQlink, Slurm, and related toolchains.
Be responsible for the reliability, performance, administrations, and lifecycle management of the Quantum environment, including Linux systems, QPU hardware, job schedulers (e.g., Slurm), networking, containerized applications, and storage.
Work closely with networking and facilities teams to ensure power, cooling, timing, environmental controls, and low-latency connectivity meet quantum hardware requirements.
Serve as a technical interface to quantum hardware partners, collaborating on system bring-up, connectivity, control interfaces, and co-design opportunities.
Help define hosting, systems architecture, and integration requirements for new quantum systems entering the facility.
Partner with internal researchers and engineers to deploy, optimize, and benchmark hybrid workloads across simulation, quantum error correction, calibration, optimization, and machine learning.
Prototype, document, and evaluate end-to-end workflows that demonstrate the capabilities of the platform.
Support researchers with application solving and standard methodologies.