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High Performance Computing Jobs in Santa Clara, CA

Onesubsea

High Performance Computing Engineer

Sunnyvale, CA · On-site

$120 - $160/hr

We are seeking a highly skilled High Performance Computing (HPC) Engineer with a strong background in modeling and solving complex discrete optimization problems. The ideal candidate will demonstrate ...

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$116.9K

$180.2K

How much do high performance computing jobs pay per year?

As of Sep 5, 2026, the average yearly pay for high performance computing in Santa Clara, CA is $116,851.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,900.00 and $147,900.00 per year, depending on experience, location, and employer.

What is high performance computing?

A High Performance Computing (HPC) job involves designing, managing, and optimizing advanced computing systems used for complex calculations, simulations, and data processing. Professionals in this field work with supercomputers, parallel computing frameworks, and high-speed networks to enhance computational efficiency. HPC specialists are commonly employed in scientific research, engineering, finance, and artificial intelligence to solve large-scale problems. Responsibilities often include developing algorithms, maintaining HPC clusters, and improving system performance.

What are the typical responsibilities of someone working in high performance computing?

Professionals in High Performance Computing (HPC) are often responsible for designing, implementing, and maintaining powerful computing clusters tailored for processing large data sets or running complex simulations. Daily tasks may include optimizing code and workflows for parallel environments, troubleshooting hardware and software issues, and supporting researchers or engineers in using HPC resources efficiently. Collaboration is common, as HPC specialists work closely with IT staff, domain scientists, and software developers to ensure systems meet project and organizational goals. This role provides a challenging and dynamic work environment, offering opportunities to continually learn about emerging technologies and methodologies in computational science.

What are the key skills and qualifications needed to thrive in high performance computing, and why are they important?

To thrive in High Performance Computing, you need expertise in parallel computing, computer architecture, and programming languages such as C/C++ or Fortran, often backed by a relevant degree in computer science or engineering. Familiarity with HPC cluster management, job scheduling systems (e.g., SLURM), and experience with accelerators like GPUs or cloud platforms is crucial; certifications in Linux administration or HPC technologies are advantageous. Strong problem-solving skills, attention to detail, and effective communication abilities help professionals excel in complex, collaborative environments. These qualifications enable the efficient design, deployment, and maintenance of advanced computing infrastructure to support scientific and engineering applications.

Is high performance computing still relevant?

High Performance Computing (HPC) remains highly relevant as it enables complex data processing, scientific simulations, and large-scale analytics across industries such as research, finance, and technology. HPC specialists with skills in parallel programming, cluster management, and relevant tools like MPI or CUDA are in demand to support advancements in AI, climate modeling, and big data analysis.

What are examples of high performance computing?

High Performance Computing (HPC) involves using powerful supercomputers and parallel processing techniques to solve complex computational problems. Examples include climate modeling, molecular simulations, financial risk analysis, and large-scale data processing in scientific research. HPC jobs often require knowledge of programming languages like C++ or Fortran, and familiarity with cluster management and parallel computing frameworks such as MPI or OpenMP.

What are the most commonly searched types of High Performance Computing jobs in Santa Clara, CA?

The most popular types of High Performance Computing jobs in Santa Clara, CA are:

What are popular job titles related to High Performance Computing jobs in Santa Clara, CA?

For High Performance Computing jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching High Performance Computing jobs in Santa Clara, CA look for?

The top searched job categories for High Performance Computing jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for High Performance Computing jobs?

Cities near Santa Clara, CA with the most High Performance Computing job openings:

High Performance Computing jobs near you
Infographic showing various High Performance Computing job openings in Santa Clara, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $116,889 per year, or $56.2 per hour.

High Performance Computing Engineer

Onesubsea

Sunnyvale, CA • On-site

$120 - $160/hr

Other

Posted 4 days ago

Job description

We are seeking a highly skilled High Performance Computing (HPC) Engineer with a strong background in modeling and solving complex discrete optimization problems. The ideal candidate will demonstrate deep expertise in operations research, advanced mathematical programming, and quantum computing technologies. Your solutions will address challenges such as scheduling, logistics, resource allocation, object placement, bin packing and inversion for large, data-driven systems demanding exceptional performance and precision.

Key Responsibilities
  • Design, implement, and optimize algorithms to solve large-scale discrete optimization problems, including scheduling, logistics, resource allocation, object placement, bin packing and inversion.
  • Apply advanced operations research techniques using linear programming, quadratic programming, and combinatorial optimization.
  • Develop and deploy heuristic and metaheuristic approaches (e.g., simulated annealing, genetic algorithms, Tabu search) for intractable or non-convex problems.
  • Leverage high-performance computing environments to scale and accelerate problem-solving, including multi-core, distributed, and cloud architectures.
  • Utilize quantum computing hardware (quantum annealers, gate model devices) and quantum-inspired technologies for problem modeling, algorithm implementation, and performance benchmarking.
  • Collaborate with data scientists, software engineers, and domain experts to identify requirements, formulate models, and integrate solutions into operational workflows.
  • Conduct performance analysis, benchmarking, and continuous improvement of optimization solvers and pipelines.
  • Stay abreast of emerging trends in quantum computing, operations research, and HPC to ensure the use of cutting-edge techniques.
Required Qualifications
  • Advanced degree (MS/PhD) in Computer Science, Operations Research, Applied Mathematics, Physics, Engineering, or related fields.
  • Proven experience (3+ years preferred) tackling discrete optimization problems at scale, with a portfolio demonstrating end-to-end model implementation and solution.
  • Hands‑on expertise in linear and quadratic programming, solver technologies (CPLEX, Gurobi, or equivalent).
  • Proficiency with heuristic/metaheuristic optimization techniques (simulated annealing, genetic algorithms, Tabu search, etc.).
  • Demonstrated experience with quantum computing technologies: quantum annealing (e.g., D‑Wave), gate model platforms (e.g., IBM Qiskit, Google Cirq), and/or quantum-inspired optimization solvers.
  • Ability to work in high performance/distributed computing environments (HPC clusters, parallel programming, large-scale simulation).
  • Proficiency with programming languages such as Python, C++, or Julia, and relevant scientific computing libraries.
  • Excellent analytical, problem‑solving, and communication skills; able to translate business needs into technical requirements.
Preferred Qualifications
  • Experience developing cross-platform optimization packages and APIs.
  • Familiarity with hybrid quantum-classical workflows.
  • Published research or open-source contributions in optimization or quantum computing fields.
  • Experience in domain-specific optimization (supply chain, logistics, manufacturing).
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