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Python Phd Hpc Jobs in Seattle, WA (NOW HIRING)

Principal Plasma Data Scientist

Everett, WA · On-site

$230K - $270K/yr

PhD in Physics, Engineering, Applied Math, Computational Science, Machine Learning, or related ... Python, or similar; Fortran or HPC exposure valuable) * Familiarity with magnetic diffusion ...

PhD or Master's degree in Computer Science, Software Engineering, or equivalent experience. * 4+ ... HPC, networking, and AI applications. * Hands-on experience developing and deploying various ...

Senior Power Engineer

Redmond, WA · On-site

$160K - $261K/yr

MS and PHD are preferred. * 3+ years of experience with high power redundant AC-DC power supply ... Python, Cadence, Mathcad, LTSpice, Simetrix/Simplis or PSCAD. * Excellent communication and ...

Head of Data

Everett, WA · On-site

$170K - $210K/yr

Hands-on Python experience with scientific/data libraries (NumPy, Pandas, scikit-learn, or ... PhD in physics or related field strongly preferred. Employment may be conditioned upon the ability ...

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Showing results 1-20

Python Phd Hpc information

See Seattle, WA salary details

$26.2K

$159.3K

$230.4K

How much do python phd hpc jobs pay per year?

As of Jun 8, 2026, the average yearly pay for python phd hpc in Seattle, WA is $159,291.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,800.00 and $187,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Python PhD HPC (High Performance Computing) 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 professional 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.
What job categories do people searching Python Phd Hpc jobs in Seattle, WA look for? The top searched job categories for Python Phd Hpc jobs in Seattle, WA are:
Senior Deep Learning Tools Engineer - CUDA Tile

Senior Deep Learning Tools Engineer - CUDA Tile

Nvidia

Redmond, WA

$117K - $160K/yr

Full-time

Posted 2 days ago


Job description

NVIDIA is building advanced compiler technologies to accelerate AI workloads, and we are looking for an engineer focused on performance validation, analysis, and tracking. In this role, you will work at the intersection of deep learning compilers, GPU systems, and automation infrastructure, ensuring that performance improvements are measurable, scalable, and continuously validated over time.

Do you want to help drive the performance of next-generation compilers? Are you excited by how GPU performance powers breakthroughs in deep learning, autonomous systems, and high-performance computing? We are seeking a talented Deep Learning Compiler & Tools Engineer focused on CUDA Tile (Performance & Infrastructure) to join our team.

You will collaborate closely with compiler developers, infrastructure providers, and hardware teams to build systems that track, analyze, and improve performance across rapidly evolving AI workloads. If you're passionate about performance, systems, and building infrastructure that drives real-world impact, we want to hear from you.

What You'll Be Doing:

  • Design and develop performance testing frameworks for deep learning compilers and workloads

  • Build and maintain automated pipelines (CI/CD) to continuously track performance across models, hardware, and compiler changes

  • Implement benchmarking systems to measure latency, throughput, and efficiency of AI and HPC workloads

  • Analyze performance trends over time and identify regressions, bottlenecks, and optimization opportunities

  • Partner with compiler and architecture teams to debug and resolve performance issues

  • Develop tools and dashboards for performance visualization, reporting, and insights

  • Enable scalable testing across diverse GPU systems and environments

  • Improve infrastructure to ensure reliable, reproducible, and high-signal performance data

What We Need to See:

  • BS, MS, or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field

  • 5+ years of software engineering experience, including experience in performance engineering, benchmarking, or systems optimization

  • Strong programming skills in Python (C++ is a plus)

  • Experience with CI/CD systems and automation frameworks

  • Familiarity with hardware-aware performance analysis (GPUs, accelerators, or similar systems)

  • Experience working with deep learning frameworks such as PyTorch, TensorFlow, JAX, or TensorRT

  • Background in data analysis, profiling, and regression tracking

  • Ability to debug complex system-level issues across software and hardware layers

Ways to Stand Out from the Crowd::

  • Experience with GPU performance analysis and optimization

  • Understanding of compiler internals (LLVM, MLIR, CUDA compilation flow)

  • Experience building performance dashboards and large-scale telemetry systems

  • Familiarity with hardware/software co-design or low-level performance tuning

  • Experience with distributed testing infrastructure or large-scale benchmarking systems

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered one of the most desirable employers in the technology industry. Our teams are tackling some of the most challenging problems in AI, deep learning, and accelerated computing.

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.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 10, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.#deeplearning

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