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Freelance High Performance Computing Engineer Jobs in Milpitas, CA

RadixArk

Performance Engineer

Palo Alto, CA · On-site

... high-performance computing • Familiarity with profiling tools, performance debugging, tracing ... both engineers and customers Preferred : • Experience with CUDA, Triton, Pallas, ROCm, XLA, or ...

RadixArk

Performance Engineer

Palo Alto, CA · On-site

... high-performance computing • Familiarity with profiling tools, performance debugging, tracing ... both engineers and customers Preferred : • Experience with CUDA, Triton, Pallas, ROCm, XLA, or ...

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All JobsHigh Performance Computing Engineer JobsFreelance High Performance Computing Engineer JobsFreelance High Performance Computing Engineer Jobs in Milpitas, CA

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 Aug 20, 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:

What cities near Milpitas, CA are hiring for Freelance High Performance Computing Engineer jobs?

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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.

Senior Deep Learning Performance Architect

Nvidia Corporation

Santa Clara, CA • On-site

$196K/yr

Full-time

Re-posted 17 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

We are now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics and high-performance computing applications. This position offers the chance to create a meaningful impact in a dynamic, technology-focused company.
What you will be doing:
  • As a member of our deep learning architecture team, you will craft high performance energy efficient system and processor architectures to extend the state of the art in deep learning.
  • Prototype key deep learning and data analytics algorithms and applications.
  • Analyze trade-offs in performance, cost and power developing analytical models, simulators and test suites.
  • Analyze architecture performance and/or energy efficiency considering deep learning workloads, modeling and prototyping.
  • Collaborate across the company to guide the direction of machine learning, working with software, research and product teams.

What we need to see:
  • Master's or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience.
  • 4+ years of relevant work or research experience.
  • A strong foundation in machine learning and deep learning fundamentals to complement your expertise in computer architecture.
  • A strong background in high performance power efficient designs, energy efficient high performance computing, performance analysis and profiling to identify performance bottlenecks.
  • Fluency in programming languages such as Python, C, C++.
  • Experience and familiarity with GPU computing and parallel programming models.
  • You have firsthand work experience with analytical performance modeling, profiling, and analysis.

The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Today, NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as "the AI computing company."
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you creative and seeking new challenges? If so, we want to hear from you! Come, join our DL Architecture team and help build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly growing field.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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