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Freelance High Performance Computing Engineer Jobs in North Carolina

VAST Data

Customer Support Engineer

Raleigh, NC · On-site

... and high-performance computing at customer sites and in the lab. You will work directly with ... Scripting and programming - bash scripting is required; must be familiar with one or more other ...

Nvidia

Senior Architect, Data Center Modeling

Durham, NC

$65 - $87/hr

... high-performance computing and AI technologies. What we need to see: * Bachelors degree in Computer Science, Computer Engineering, Electrical Engineering or related fields or equivalent experience ...

Drive Capital

Customer Support Engineer

Raleigh, NC · On-site

$80 - $100/hr

... and high-performance computing at customer sites and in the lab. You will work directly with ... Scripting and programming - bash scripting is required; must be familiar with one or more other ...

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ElevaIT Solutions

Site Reliability Engineer

Charlotte, NC · On-site

$55.75 - $74/hr

Site Reliability Engineer Location: Remote (US, EST hours required) Interview Process: 2x ... Experience supporting scientific research, high performance computing, or computational science ...

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Freelance High Performance Computing Engineer information

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.

What are the most commonly searched types of High Performance Computing Engineer jobs in North Carolina?

The most popular types of High Performance Computing Engineer jobs in North Carolina are:

What are popular job titles related to Freelance High Performance Computing Engineer jobs in North Carolina?

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

What job categories do people searching Freelance High Performance Computing Engineer jobs in North Carolina look for?

The top searched job categories for Freelance High Performance Computing Engineer jobs in North Carolina are:

What cities in North Carolina are hiring for Freelance High Performance Computing Engineer jobs?

Cities in North Carolina with the most Freelance High Performance Computing Engineer job openings:

Freelance High Performance Computing Engineer jobs near you

Senior Software Engineer, CUTLASS Platform

Nvidia

Durham, NC

$118K - $156K/yr

Full-time

Re-posted 19 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

NVIDIA's high-performance computing platforms are powering the AI revolution across many applications and industries. Within our software stack, CUTLASS stands out as a popular open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs.

If you are passionate about designing abstractions for Tensor Core and related GPU hardware features in MLIR, Python, and C++ that enable writing high performance kernels, apply to join the CUTLASS team today!

What you'll be doing:

  • Develop core components of the CUTLASS platform including Tensor Core MMAs, copies, synchronization barriers, schedulers, and other GPU hardware features in CUDA C++ and CUTLASS Python DSL.

  • Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes.

  • Author example kernels utilizing CUTLASS abstractions to showcase the use of novel GPU hardware features that are crucial for achieving high performance.

  • Collaborate with GPU architecture, CUDA, and NVVM/PTX compiler teams to provide feedback on programming models and to assess the performance of future GPU hardware features.

What we need to see:

  • Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).

  • 3+ years of relevant industry experience.

  • Strong proficiency in C++ programming and software design, including debugging, performance evaluation, and testing.

  • Experience working with high-performance code generation and knowledge of compiler transformations and optimizations.

  • A deep understanding of computer architecture and parallel computing programming models.

Ways to stand out from the crowd:

  • Experience writing high-performance kernels at low levels of abstractions like NVVM/ PTX for GPUs or other similar parallel processing architectures.

  • Hands-on compiler design experience, particularly in MLIR.

  • Understanding of deep learning models, algorithms, and frameworks.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us. If you're creative, autonomous, and love a challenge, consider joining our Deep Learning Library team and help us build the real-time, cost-effective 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 5, 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

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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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