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Python Phd Hpc Jobs in California (NOW HIRING)

Sr. Manager, Technical Product Management

Santa Clara, CA · On-site

$194K - $224K/yr

Familiarity with AI/ML, HPC, and large‑scale distributed systems is highly valuable. Your work ... Solid programming skills (e.g., Python, C++) for modeling and analysis. * Proven ability to ...

$100K - $500K/yr

This role is ideal for early-career architects with a strong academic background, ideally a PhD ... Strong programming skills in C++, Python, or similar languages used for architectural modeling and ...

... PhD or equivalent experience in Computer Science, Computer Engineering, or a related field. • ... NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.

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Python Phd Hpc information

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 are popular job titles related to Python Phd Hpc jobs in California? For Python Phd Hpc jobs in California, the most frequently searched job titles are:
What job categories do people searching Python Phd Hpc jobs in California look for? The top searched job categories for Python Phd Hpc jobs in California are:
What cities in California are hiring for Python Phd Hpc jobs? Cities in California with the most Python Phd Hpc job openings:
Infographic showing various Python Phd Hpc job openings in California as of July 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 91% In-person, 3% Hybrid, and 6% Remote job distribution.
Principal Machine Learning Engineer, Accelerated Apache Spark

Principal Machine Learning Engineer, Accelerated Apache Spark

NVIDIA

Santa Clara, CA • On-site

Full-time

Re-posted 21 days ago


Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies


Job description

Job Summary:
NVIDIA is looking for a Machine Learning Engineer to join the GPU accelerated Apache Spark team. This role involves designing and implementing machine learning solutions to optimize Apache Spark workloads on GPUs and collaborating with partners to deploy complex ML solutions.
Responsibilities:
• Design and implement machine learning solutions for performance prediction and optimization of GPU accelerated enterprise Apache Spark workloads.
• Develop advanced algorithms and adaptive systems to continuously improve the performance of Apache Spark workloads on GPUs.
• Develop AI-based agents and tools to assist with fixing system issues and application optimization.
• Collaborate with key partners and customers on the deployment of complex machine learning solutions in various environments.
• Maintain deep domain expertise by knowing the latest published advances in ML systems and algorithms.
• Provide technical mentorship and leadership in data science and machine learning to a team of engineers.
Qualifications:
Required:
• BS, MS, or PhD or equivalent experience in Machine Learning, Data Science, Computer Science or a closely related field.
• 12+ years of professional experience in designing, implementing, and productionizing high-quality ML/DL solutions.
• 5+ experience as technical lead in ML model development.
• Proven hands-on experience (2+ years) with large-scale data processing platforms, such as Apache Spark.
• Proven ability to employ modern tooling and sound techniques for all aspects of crafting, deploying, and maintaining machine learning models.
• Excellent programming skills in Python and Python data science related libraries like numpy, pandas, scikit-learn, scipy, pytorch, and tensorflow.
• Deep experience with sophisticated ML methodologies, including LLM/GenAI, reinforcement learning, and adaptive, on-line ML systems.
• Strong expertise in feature engineering, feature importance assessment, and developing boosted tree model solutions (e.g., XGBoost).
Preferred:
• Understanding of the internal workings and architecture related to Apache Spark.
• Familiarity with NVIDIA GPUs and CUDA.
• Experience coding in Scala, Java, and/or C++.
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

Hours and flexibility

Workplace

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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