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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 California?

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

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

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

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

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

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

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

Freelance High Performance Computing Engineer jobs near you

Senior Deep Learning Kernel Software Performance Architect

NVIDIA

Santa Clara, CA • On-site

$196K/yr

Full-time

Re-posted 7 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

Job Summary:
NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics, and high-performance computing applications. The Senior Kernel Performance Architect for Deep Learning Software will craft GPU-accelerated system architectures, prototype high-performance software, and collaborate with various teams to optimize deep learning performance.
Responsibilities:
• Craft GPU-accelerated system architectures that push the boundaries of deep learning performance.
• Prototype high-performance software for deep learning and data analytics workloads.
• Analyze, visualize, and optimize software performance using analytical models, simulators, and test suites.
• Collaborate closely across NVIDIA teams such as:
• CUDA Compiler teams to identify performance issues.
• AI/ML training and inference performance teams to identify and optimize critical deep learning layers.
• hardware architecture performance teams to define expectation for emerging deep learning hardware features.
Qualifications:
Required:
• A Master's or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience.
• 5+ years of relevant industry 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 kernel (such as CUTLASS), work experience on math library 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.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

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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