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Deloitte

Audits companies and advises on tax and technology

Quantum Computing – Senior Applied Research Scientist - Multiple Teams

AI ResearchPosted on Nov 9
Full-timeRosslyn, Arlington, VA, USA$134.5k - $265.1k

About the Job

Requirements

  • A doctoral degree in Physics, Applied Mathematics, Computer Science, Quantum Information Science, Electrical Engineering, Operations Research, or a related field is required.
  • The candidate must possess or be willing to seek, obtain, and maintain a U.S. government security clearance.
  • At least 5 years of relevant research or development experience is required, including independently leading technically complex work from problem framing through analysis and communication of conclusions.
  • The candidate must have expertise in tensor network methods such as matrix product state (MPS), density matrix renormalization group (DMRG), time-evolving block decimation (TEBD), projected entangled pair states (PEPS), tree tensor networks, or tensor train decompositions, including bond-dimension control, truncation-error analysis, and contraction-path optimization.
  • The candidate must have a strong foundation in numerical methods, optimization, randomized numerical linear algebra, and quantum-inspired methods for machine learning.
  • The candidate must be able to formulate real-world problems and assess when structural characteristics such as low entanglement, low rank, sparsity, or operator locality make them suitable for quantum-inspired approaches.
  • The candidate must be able to design fair and rigorous benchmarks using strong baselines, appropriate tuning, controlled compute budgets, transparent metrics, and honest reporting of positive and negative results.
  • The candidate must have strong Python skills and experience implementing, reproducing, or critically evaluating algorithms using scientific and quantum software such as NumPy, SciPy, JAX, PyTorch, Quimb, ITensor, Cotengra, Qiskit, Cirq, or PennyLane.
  • The candidate must be able to translate technical research into client-relevant insights, business value, prototypes, roadmaps, or offering priorities.
  • The candidate must demonstrate technical contributions in quantum-inspired computing, tensor networks, classical simulation, or optimization through publications, preprints, open-source contributions, community benchmarks, conference presentations, or other evidence.
  • The candidate must have strong written and verbal communication skills to explain complex technical findings, uncertainty, tradeoffs, and recommendations to technical and business audiences.
  • The candidate must be able to guide collaborators, provide constructive technical feedback, and work across research, engineering, product, and business teams.
  • The candidate must be able to travel up to 10%, based on business needs and the clients and industries served.
  • The candidate must be legally authorized to work in the United States without employer sponsorship, now or at any time in the future.

Responsibilities

  • Work with national security and domain specialists to translate mission challenges into mathematical models and computational problems, including potential research in uncertainty quantification, rare-event analysis, resilient infrastructure and supply chains, probabilistic inference, and dynamical systems.
  • Determine how dependencies, correlations, network topology, and tensor representations affect computational cost and accuracy, and identify where tensor network approaches are promising or limited.
  • Design, implement, and optimize quantum-inspired algorithms, including tensor network, Pauli-propagation, dequantized, Ising, and QUBO-based methods, using high-performance computing and GPU resources where appropriate.
  • Collaborate with engineers to improve performance on CPU, GPU, and high-performance computing platforms.
  • Contribute technical expertise to government proposals and collaborations.
  • Move validated research from proof of concept to prototype to reusable product assets, including solver and simulator libraries, experiment frameworks, benchmarks, and engineering requirements, in partnership with product and engineering teams.
  • Serve as a technical subject-matter expert in client discussions, executive briefings, proposals, demonstrations, and ecosystem collaborations, communicating results, limitations, uncertainty, and risks.
  • Mentor researchers and engineers, provide constructive technical review, and establish standards for research rigor, reproducibility, software quality, and communication.
  • Support work involving government agencies, national laboratories, academic groups, vendors, and other clearance-sensitive stakeholders in accordance with applicable clearance and information-handling requirements.

Desired Qualifications

  • Research extending tensor networks to applications beyond quantum many-body physics, such as uncertainty quantification, numerical integration, probabilistic graphical models, stochastic processes, differential equations, optimization, or machine learning.
  • Experience developing new tensor representations, network architectures, contraction algorithms, or methods for controlling approximation error.
  • Expertise in one or more complementary areas, such as probability and statistics, stochastic modeling, dynamical systems, optimal control, numerical analysis, or computational physics.
  • Experience with GPU acceleration, parallel computing, or distributed scientific workloads using tools such as JAX, PyTorch, CUDA, cuTensorNet, MPI, or related technologies.
  • Experience with scientific tensor software such as Quimb, ITensor, Cotengra, or comparable libraries.
  • Experience applying computational methods to national security problems, including infrastructure resilience, logistics and supply chains, sensing, materials, or modeling complex systems under uncertainty.
  • Experience collaborating with government agencies, national laboratories, academic researchers, or multidisciplinary research teams.
  • Experience developing research proposals, helping define a research agenda, or transitioning research software to broader use.
  • Familiarity with quantum algorithms or quantum simulation where relevant to the research.

About the Company

Deloitte

Audits companies and advises on tax and technology

Deloitte audits companies and advises businesses and governments on tax, technology, and risk, and it is one of the Big Four, the world's four largest accounting firms. In 1849 its founder became the first independent auditor of a public company, Britain's Great Western Railway. Its auditors check companies' financial reports for errors and fraud before investors rely on them, while its consultants design strategy, install business software, and defend clients against cyberattacks. Clients pay fees for each audit or project, and each country's Deloitte firm is a separate business owned by its local partners. Deloitte was founded in London in 1845 and is based in New York.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$17.1M
Headquarters
New York, NY
Founded
1845

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