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Freelance High Performance Computing Engineer Jobs in Milpitas, CA

Onesubsea

High Performance Computing Engineer

Sunnyvale, CA · On-site

$125 - $150/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 ...

SLB

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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Freelance High Performance Computing Engineer information

See Milpitas, CA salary details

$62.3K

$153.1K

$225.5K

How much do freelance high performance computing engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for freelance high performance computing engineer in Milpitas, CA is $153,070.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,400.00 and $171,900.00 per year, depending on experience, location, and employer.

What is a freelance high performance computing engineer?

A Freelance High Performance Computing (HPC) Engineer is a professional who specializes in designing, implementing, and optimizing computing systems that handle complex, large-scale computations. They work independently or on a contract basis for different organizations, helping to develop and maintain supercomputers, clusters, and parallel processing applications. Their expertise is often sought in fields like scientific research, finance, artificial intelligence, and engineering where processing large datasets quickly is essential. Freelancers in this field typically possess strong programming skills, knowledge of HPC architectures, and experience with performance tuning and troubleshooting.

What are the key skills and qualifications needed to thrive as a freelance high performance computing engineer?

To thrive as a Freelance High Performance Computing Engineer, you need expertise in parallel programming, cluster management, and a strong background in computer science or engineering. Familiarity with tools such as MPI, OpenMP, Linux environments, and cloud-based HPC platforms, along with certifications in cloud services or HPC technologies, is highly beneficial. Excellent problem-solving, project management, and communication skills set top freelancers apart when working with diverse clients. These competencies ensure the delivery of optimized, scalable solutions and effective collaboration in complex technical projects.

How do freelance high performance computing engineers typically collaborate with client teams during projects?

Freelance HPC Engineers often work closely with client engineering, research, or IT teams to design, implement, and optimize computational solutions. Collaboration usually occurs through regular virtual meetings, code reviews, and progress updates to ensure alignment with project goals and technical requirements. Clear communication and documentation are essential, as freelancers may need to integrate their work into larger systems or hand off projects to in-house teams. Building strong relationships and understanding the client's workflow help ensure successful project delivery and can lead to ongoing opportunities.

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

AspectFreelance High Performance Computing EngineerFreelance Data Scientist
CredentialsAdvanced degrees in computer science, engineering, or related fields; knowledge of HPC systemsDegree in data science, statistics, or related fields; proficiency in programming and analytics
Work EnvironmentSpecialized computing clusters, research labs, or cloud HPC platformsData analysis environments, cloud platforms, and business analytics tools
Industry UsageResearch institutions, scientific computing, engineering simulations
Search & Comparison IntentFocus on high-performance computing tasks, technical skills

While both roles involve advanced technical skills, Freelance High Performance Computing Engineers specialize in optimizing and managing large-scale computing resources for scientific and engineering applications. Freelance Data Scientists focus on analyzing data to extract insights for business or research purposes. The key difference lies in their core focus: HPC engineers work with hardware and system performance, whereas data scientists work with data analysis and modeling.

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For Freelance High Performance Computing Engineer jobs in Milpitas, CA, the most frequently searched job titles are:

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The top searched job categories for Freelance High Performance Computing Engineer jobs in Milpitas, CA are:

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Freelance High Performance Computing Engineer jobs near you
Infographic showing various Freelance High Performance Computing Engineer job openings in Milpitas, CA as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $153,070 per year, or $73.6 per hour.

High Performance Computing Engineer

Sunnyvale, CA • On-site

Onesubsea
See more jobs at Onesubseaexternal

$125 - $150/hr

Other

Posted 7 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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