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Freelance High Performance Computing Engineer Jobs in California

Cynet Systems

HPC Consultant

Fremont, CA · On-site

$52 - $57/hr

High Performance Computing Engineer Pay Range: $52hr - $57hr Responsible for designing, optimizing, and supporting high-performance computing (HPC) environments including cluster scheduling, storage ...

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Freelance High Performance Computing Engineer information

How do freelance High Performance Computing (HPC) 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 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, and why are they important?

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.

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.

What are the most commonly searched types of High Performance Computing Engineer jobs in California? The most popular types of High Performance Computing Engineer jobs in California are:
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Freelance High Performance Computing Engineer jobs near you

Software Engineer - Nonlinear Solid Mechanics & High-Performance Computing

Vinci AI

Palo Alto, CA • On-site

$190K - $230K/yr

Full-time

Posted 6 days ago

Job description

About Us
At Vinci4d, we are building the next generation of simulation software for thermal, fluid flow, and structural mechanics applications - the kind of tools that change how engineers design products, from the first mesh to the final answer. We are a small, technically deep team that moves fast, ships real software, and takes on hard problems that matter. If you want your work to be foundational to a platform used by engineers worldwide, this is the place.
The Role
We are looking for a software engineer who lives at the intersection of computational solid mechanics, numerical methods, and high-performance computing. You will design, implement, and tune solvers for geometric and material nonlinearity in solid mechanics - think large-deformation, contact, and history-dependent material response - that run at scale on modern hardware. You will write production-quality code, contribute to our CI/CD infrastructure, and collaborate closely with a multi-disciplinary team of physicists, engineers, and software developers.
This is not a "maintain the existing stack" role. You will be building things that don't exist yet, solving problems that require both rigorous mathematical thinking and solid engineering instincts.
What You Will Work On
  • Develop and tune nonlinear solvers for solid mechanics, handling both geometric nonlinearity (large deformation, finite strain) and material nonlinearity (plasticity, viscoelasticity, temperature-dependent and history-dependent constitutive models)
  • Build and optimize the underlying linear algebra: iterative linear solvers and preconditioners for the large sparse systems arising at each Newton iteration
  • Port and optimize these solvers for GPU execution using CUDA, HIP, or equivalent frameworks, with a focus on memory bandwidth, occupancy, and scalability
  • Implement FEM discretizations for structural and thermomechanical field solves, with attention to robustness and convergence under stiff, ill-conditioned, and near-singular conditions
  • Contribute to a robust software engineering foundation: version control discipline, automated testing, CI/CD pipelines, and code review practices
  • Collaborate with domain experts to translate physical models and mathematical formulations into correct, efficient implementations
  • Profile and benchmark solver performance; identify and eliminate bottlenecks

What We Are Looking For
Technical Skills
  • Hands-on experience developing solvers for geometric and material nonlinearity in solid mechanics - large-deformation kinematics, nonlinear constitutive models, and the Newton-type schemes that drive them to convergence
  • Strong foundation in the finite element method (FEM) for solid and structural mechanics
  • Deep familiarity with iterative linear solvers (e.g., Krylov methods) and preconditioning techniques for large, sparse systems, with hands-on experience implementing these inside a nonlinear solver
  • Proven GPU programming experience (CUDA, HIP, SYCL, or similar) with a track record of getting real performance out of hardware
  • Proficiency in C++ and/or Python; comfort working in performance-critical codebases
  • Strong software engineering practices: Git workflows, code review, automated testing (unit, integration, regression), and CI/CD pipelines

Experience
  • 3-6 years of industry or research experience in a relevant field (computational mechanics, scientific computing, computational physics, numerical simulation, or HPC)
  • A portfolio of work - open source contributions, published code, or shipped products - that demonstrates the above

Soft Skills
  • A genuine collaborator: you learn from teammates as readily as you help them
  • Able to communicate technical depth clearly to people from different disciplines - physicists, mechanical engineers, product managers
  • Comfortable with ambiguity and excited by the challenges that come with building something new
  • Self-directed and ownership-oriented: you drive your work to completion without needing to be managed closely

Nice to Have
  • Experience with warpage and residual-stress problems in semiconductor manufacturing (e.g., packaging, die/substrate stacks, thermomechanical deformation)
  • Familiarity with matrix-free methods for nonlinear and linear operator application
  • Experience with geometric multigrid approaches as solvers or preconditioners
  • Background in adaptive mesh refinement (AMR)
  • Familiarity with embedded geometry or immersed boundary methods for solid mechanics
  • Experience applying machine learning to solid mechanics problems (surrogates, constitutive modeling, solver acceleration)
  • Experience with performance profiling tools (Nsight, VTune, Roofline analysis)

Why Vinci4d
  • Work on genuinely hard technical problems with real engineering impact
  • Join a small team where your contributions are visible and your voice is heard
  • Competitive compensation with equity participation
  • Flexible work environment
  • The satisfaction of building something from the ground up - and the opportunity to help define what it becomes

Apply