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Python Phd Hpc Jobs in Santa Clara, CA (NOW HIRING)

NVIDIA

Neural Graphics Engineer

Santa Clara, CA · On-site

$164K - $203K/yr

Required : • BS, MS, or PhD in Computer Science, Electrical Engineering, Physics, or a related ... NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.

Nvidia

Senior CPU Performance Architect

Santa Clara, CA · On-site

$196K/yr

Study workloads for a wide range of markets, including CSP, HPC,AI / DL, and autonomous vehicles ... PhD or research experience * Experience with performance programming and software optimization.

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How much do python phd hpc jobs pay per year?

As of Aug 10, 2026, the average yearly pay for python phd hpc in Santa Clara, CA is $164,387.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,800.00 and $193,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Python PhD HPC specialist, and why are they important?

To excel as a Python PhD HPC specialist, you need advanced knowledge of Python programming, parallel computing concepts, and a doctoral degree in a computationally intensive field. Familiarity with HPC clusters, job schedulers like SLURM, and libraries such as NumPy, SciPy, and MPI for Python is typically required. Strong analytical thinking, problem-solving, and collaboration skills set candidates apart in this role. These competencies ensure efficient development, optimization, and deployment of large-scale computational models that drive scientific research and innovation.

What are the typical challenges faced by a Python PhD HPC specialist when working on large-scale computational projects?

Professionals in a Python PhD HPC role often encounter challenges related to optimizing Python code for high-performance computing environments, particularly when scaling computations across multiple nodes or clusters. Managing memory usage, debugging parallel code, and ensuring compatibility with various HPC libraries and frameworks are common hurdles. Additionally, effective collaboration with interdisciplinary teams—such as domain scientists, system administrators, and data engineers—is crucial for project success. Staying updated with advancements in both Python and HPC technologies also requires ongoing learning and adaptability.

What is a Python PhD HPC specialist?

A Python PhD HPC specialist is a professional with a doctoral degree who uses the Python programming language to develop and optimize high-performance computing (HPC) applications. These specialists often work on complex scientific or engineering problems that require significant computational resources, such as simulations, data analysis, or machine learning at scale. They possess deep expertise in both Python programming and HPC environments, including parallel computing, distributed systems, and cluster management. Their work often bridges the gap between theoretical research and practical implementation on supercomputers or large compute clusters.
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Senior System Software Engineer - GPU Performance

NVIDIA

Santa Clara, CA • On-site

Full-time

Re-posted 22 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

Job Summary:
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The role involves conducting performance characterization and analysis on large multi-GPU and multi-node clusters to influence the roadmap of communication libraries.
Responsibilities:
• Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters.
• Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack
• Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available
• Triage and root-cause performance issues reported by our customers
• Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information
• Collaborate with a very dynamic team across multiple time zones
Qualifications:
Required:
• M.S. (or equivalent experience) or PhD in Computer Science, or related field with relevant performance engineering and HPC experience
• 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM)
• Experience conducting performance benchmarking and triage on large scale HPC clusters
• Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)
• Implement micro-benchmarks in C/C++, read and modify the code base when required
• Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python
• Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker)
• Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones
Preferred:
• Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control
• Experience debugging network issues in large scale deployments
• Familiarity with CUDA programming and/or GPUs
• Experience with Deep Learning Frameworks such PyTorch, TensorFlow
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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