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High Performance Computing Hpc Jobs in California

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High Performance Computing Engineer

Sunnyvale, CA · On-site

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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High Performance Computing Hpc information

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$32.1K

$67.4K

$110.5K

How much do high performance computing hpc jobs pay per year?

As of Sep 11, 2026, the average yearly pay for high performance computing hpc in California is $67,355.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,300.00 and $81,900.00 per year, depending on experience, location, and employer.

What is high performance computing (HPC)?

High Performance Computing (HPC) refers to the use of supercomputers and parallel processing techniques to solve complex computational problems quickly and efficiently. HPC systems combine the power of multiple processors to perform billions or even trillions of calculations per second, making them essential for scientific research, engineering simulations, data analytics, and other demanding tasks. These systems are used in fields such as weather forecasting, molecular modeling, financial modeling, and artificial intelligence. By leveraging HPC, organizations can tackle problems that are too large or complex for standard computers.

What are the key skills and qualifications needed to thrive as a high performance computing (HPC) specialist?

To thrive as a High Performance Computing (HPC) specialist, you need a solid background in computer science or engineering, strong programming skills (especially in languages like C, C++, or Python), and expertise in parallel computing and Linux systems. Familiarity with cluster management tools, job schedulers (e.g., SLURM or PBS), and experience with HPC libraries and accelerators such as MPI, OpenMP, and GPU programming are typically required. Excellent problem-solving abilities, teamwork, and effective communication skills help you collaborate with researchers and resolve complex technical challenges. These competencies are vital for optimizing computational workflows, maintaining robust systems, and enabling advanced scientific or industrial research.

What are some common challenges faced by professionals working in high performance computing (HPC) environments?

Professionals in HPC roles often encounter challenges such as optimizing code for parallel processing, managing complex and rapidly evolving hardware architectures, and troubleshooting large-scale distributed systems. Collaborating closely with researchers and domain experts is also essential to ensure that computational resources are used efficiently and effectively. Keeping up with advances in both hardware and software, as well as balancing multiple projects with tight deadlines, are typical aspects of the HPC work environment.

What is the difference between High Performance Computing Hpc vs Data Scientist?

AspectHigh Performance Computing (HPC)Data Scientist
Required credentialsDegree in Computer Science, Engineering, or related fields; often certifications in parallel computing or HPC systemsDegree in Data Science, Statistics, Computer Science, or related fields; certifications in data analysis or machine learning
Work environmentSupercomputing centers, research labs, large enterprises with high computational needsTech companies, finance, healthcare, research institutions, often in office or remote settings
Industry usageScientific research, simulations, modeling, large-scale data processingData analysis, predictive modeling, machine learning, business insights

While both roles involve working with large datasets and complex computations, HPC specialists focus on designing and maintaining high-performance computing systems for scientific and engineering tasks. Data scientists analyze data to extract insights and build models. The roles often overlap in data processing but differ in technical focus and environment.

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What job categories do people searching High Performance Computing Hpc jobs in California look for?

The top searched job categories for High Performance Computing Hpc jobs in California are:

What cities in California are hiring for High Performance Computing Hpc jobs?

Cities in California with the most High Performance Computing Hpc job openings:

High Performance Computing Hpc jobs near you
Infographic showing various High Performance Computing Hpc job openings in California as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $67,355 per year, or $32.4 per hour.

High Performance Computing Engineer

Sunnyvale, CA • On-site

Onesubsea
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This job post has expired today. Applications are no longer accepted.

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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