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Quantum Computing Nvidia Jobs (NOW HIRING)

Nvidia

OR · On-site

$126K - $166K/yr

... computing. We're looking for a technical and passionate product manager to join the NVIDIA team ... This role is responsible for leading some of our newest quantum chemistry math libraries, which are ...

Nvidia

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More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a ... quantum cryptography implications. * Hands-on understanding of AI security risks combined with ...

Nvidia

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The team's charter expands into emerging domains including quantum computing interconnects. This Principal Architect role leads the research agenda and architectural direction for how NVIDIA's AI ...

Nvidia

OR · On-site

$129K - $175K/yr

An applied research team within NVIDIA's Networking Systems & Software Architecture group is ... The team's charter expands into emerging domains including quantum computing interconnects. The ...

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How much do quantum computing nvidia jobs pay per year?

As of Jun 5, 2026, the average yearly pay for quantum computing nvidia in the United States is $111,938.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,000.00 and $128,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Quantum Computing Specialist at Nvidia, and why are they important?

To thrive as a Quantum Computing Specialist at Nvidia, you need a strong background in quantum mechanics, computer science, and advanced mathematics, typically supported by a graduate degree in a related field. Experience with quantum programming languages (such as Qiskit or Cirq), familiarity with Nvidia's CUDA platform, and understanding of high-performance computing systems are essential. Strong problem-solving abilities, collaboration, and effective communication distinguish top performers in this role. These skills are critical for advancing quantum algorithms and integrating them with cutting-edge GPU technology to drive innovation in quantum computing.

How does a Quantum Computing role at Nvidia typically collaborate with cross-functional teams to drive innovation?

In a Quantum Computing role at Nvidia, you will frequently collaborate with interdisciplinary teams, including hardware engineers, software developers, and research scientists. The nature of quantum computing projects often requires integrating quantum algorithms with Nvidia’s GPU architectures, so close communication with both hardware and software divisions is essential. You may also engage with external academic partners and industry collaborators to stay at the forefront of research and accelerate the development of quantum solutions. This collaborative environment fosters innovation and provides opportunities to contribute to groundbreaking advancements in quantum and classical computing.

What is a Quantum Computing Engineer at Nvidia?

A Quantum Computing Engineer at Nvidia is a professional who works on developing hardware, software, and algorithms to enable quantum computing applications, often leveraging Nvidia's GPU technologies. They collaborate with researchers, software developers, and hardware engineers to accelerate quantum computing research and integrate quantum systems with existing high-performance computing (HPC) infrastructure. Their work may include building quantum simulators, optimizing quantum algorithms, and developing tools that bridge classical and quantum computing. Nvidia's quantum computing team is at the forefront of exploring how GPUs can support quantum workloads and advance the field.

What is the difference between Quantum Computing Nvidia vs Quantum Software Engineer?

AspectQuantum Computing NvidiaQuantum Software Engineer
Required CredentialsBachelor's or Master's in Computer Science, Physics, or related; knowledge of quantum hardwareBachelor's or Master's in Computer Science, Physics, or related; programming skills in quantum languages
Work EnvironmentTech companies focusing on hardware development and quantum hardware integrationResearch labs, tech firms, or startups developing quantum algorithms and software
Industry UsageHardware manufacturing, hardware-software integration, AI, and high-performance computingAlgorithm development, software simulation, and application of quantum computing principles

While both roles require a strong background in quantum computing and related credentials, Quantum Computing Nvidia primarily focuses on hardware development and integration within Nvidia's ecosystem. In contrast, Quantum Software Engineers concentrate on developing algorithms and software applications for quantum computers. Both roles are vital in advancing quantum technology but differ in their core responsibilities and work environments.

Sr Technical Product Manager - HPC Integration

Sr Technical Product Manager - HPC Integration

QuEra Computing, Inc.

Boston, MA • Hybrid

$170K - $250K/yr

Other

Posted 12 days ago

Job description

 
1. Mission of the Role
To define, validate, and execute the integration strategy for QuEra's quantum systems within classical HPC/AI infrastructure - identifying use cases, technical requirements, and the right ecosystem partners across the full value chain.
 
2. Core ResponsibilitiesA. Use Case Discovery & Technical Research
  • Deeply study academic and industry papers on quantum-classical hybrid workflows, quantum HPC/AI Data center integration, and the accelerations of AI for Science/Quantum discovery via quantum computing.
  • Identify high-value use cases (e.g., quantum chemistry, materials discovery, cryptoanalysis, optimization) relevant to HPC and AI centers
  • Translate theoretical research into practical product requirements - what integration, APIs, or software layers are needed to run these use cases.
  • Collaborate with research teams to maintain technical credibility when engaging HPC customers or partners.
  • Co-design solutions with lighthouse customers to verify the feasibility
A. Value Chain Mapping
  • Use the HPC value chain framework (hardware integration data center middleware workloads services) to:
  • Map current players (AWS, HPE, NVIDIA, etc.) and their quantum readiness.
  • Identify where quantum computing fits within this chain (e.g., as accelerator hardware, a cloud service, or a hybrid scheduler layer).
  • Define which layers QuEra should own vs. partner - e.g.:
  • Own: Quantum hardware, quantum control stack.
  • Partner: Data center operations, cloud orchestration, middleware, hybrid execution APIs.
B. Requirements Definition
  • Gather technical and operational requirements from HPC and AI center operators:
  • Power, cooling, networking, physical integration.
  • Scheduler integration (Slurm, PBS, AWS Batch, Kubernetes).
  • Security, compliance, and monitoring needs.
  • Define product specifications for Quantum-Classical Integration Interfaces (QCII) - the APIs, SDKs, and orchestration layers that enable hybrid workloads.
C. Partner Identification & Engagement
  • Build a partner map for each value chain layer:
  • Hardware partners: compute (NVIDIA, AMD, ARM), interconnect (Infiniband), storage (DDN, AWS FSx).
  • Cloud/HPC providers: AWS, Microsoft Azure, Google Cloud, HPE Cray, NVIDIA DGX Cloud.
  • System Integrators: Dell, HPE
  • Middleware/software partners: Slurm
  • Application/industry partners
  • Lead technical discussions and joint proof-of-concept programs with selected partners.
  • Evaluate integration options - e.g., on-prem quantum node vs. cloud-connected quantum service.
D. Product Strategy & Roadmapping
  • Define a phased integration roadmap for quantum into HPC centers and AI data center:
  • Simulation stage: Run QuEra simulators on HPC clusters.
  • Hybrid orchestration stage: Enable joint scheduling of classical + quantum workloads.
  • Native quantum accelerator stage: Deploy QuEra hardware within HPC/AI center or connect over high-speed link.
  • Balance build/partner decisions at each stage, ensuring scalability and differentiation.
F. Communication & Stakeholder Management
  • Act as the bridge between technical R&D, engineering, business development, and external partners.
  • Create clear documentation (requirements docs, partner briefs, integration specs).
  • Communicate effectively with HPC operators and enterprise customers (translating quantum complexity into operational language).
 
3. Key Skills and BackgroundTechnical Depth: Background in physics, computer engineering, or computational science; understanding of quantum computing principles and HPC architecture (Slurm, MPI, GPUs, network topology).
Product Management: Experience defining product requirements, roadmaps, and partner strategies in deep tech or HPC environments.
Ecosystem Awareness: Knowledge of cloud and data center ecosystems - AWS, NVIDIA, Intel, HPE, etc.
Cross-Functional Leadership: Ability to collaborate with quantum hardware engineers, software developers, and business teams.
Partnering & Alliances: Experience building technical partnerships and evaluating technology fit.
Communication: Skilled at simplifying deep-technical material for non-specialist executives and partners.
 
4. Success Metrics
  • A complete map of the HPC/AI ecosystem relevant to quantum integration.
  • Clear technical and operational requirements for deploying QuEra hardware in HPC centers.
  • At least 2-3 strategic technical partnerships (e.g., with AWS, HPE, or NVIDIA).
  • Defined build-vs-partner strategy for each value chain layer.
  • Delivery of hybrid quantum-classical prototype or proof-of-concept within HPC environment.

The approximate base salary range for this position is $170,000-250,000.

QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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