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Entry Level High Performance Computing Engineer Jobs in California

The AI Engineer will work closely with the founding team to build, optimize, and maintain the ... Develop and optimize high-performance computing (HPC) infrastructure. * Integrate AI models into ...

Zealogics Inc is seeking an HPC Engineer. The primary responsibilities include maintaining and ... Responsibilities : • Candidates should have good domain knowledge in High-Performance Computing ...

... entry-level candidates looking to grow their careers in High Performance Computing (HPC), Linux ... Communicate system status and issues with operations and engineering teams * Conduct physical ...

... entry-level candidates looking to grow their careers in High Performance Computing (HPC), Linux ... Communicate system status and issues with operations and engineering teams * Conduct physical ...

Experience with high-performance computing or GPU-accelerated applications. * Experience optimizing workloads across different GPU architectures. * Background in graphics, compute shaders, or AI/ML ...

Experience with high-performance computing or GPU-accelerated applications. * Experience optimizing workloads across different GPU architectures. * Background in graphics, compute shaders, or AI/ML ...

Experience with high-performance computing or GPU-accelerated applications. * Experience optimizing workloads across different GPU architectures. * Background in graphics, compute shaders, or AI/ML ...

Showing results 41-60

Entry Level High Performance Computing Engineer information

What is an entry level high performance computing engineer?

An Entry Level High Performance Computing (HPC) Engineer is a professional who assists in designing, building, and maintaining high-speed computing systems used for complex computations and large-scale data analysis. They typically work with supercomputers or computer clusters in fields like scientific research, finance, or engineering. Responsibilities often include configuring hardware, optimizing software, and troubleshooting system issues, usually under the guidance of more experienced engineers. Entry-level engineers may also help monitor system performance and support users in running high-performance applications.

What are some common challenges faced by entry level high performance computing engineers, and how can new hires successfully navigate them?

Entry level HPC engineers often encounter challenges such as working with complex parallel computing architectures, optimizing code for performance, and troubleshooting across large-scale, distributed systems. New hires may also need to quickly learn job-specific tools and adapt to rapidly evolving hardware and software environments. To navigate these challenges, it’s important to proactively seek mentorship, participate in team code reviews, and continuously build your skills through hands-on experience and training opportunities. Open communication and collaboration with experienced team members also play a key role in overcoming technical hurdles and growing within the HPC field.

What are the key skills and qualifications needed to thrive as an entry level high performance computing engineer, and why are they important?

To thrive as an Entry Level High Performance Computing Engineer, you typically need a solid background in computer science or engineering, familiarity with parallel computing concepts, and proficiency in programming languages like C/C++ or Python. Experience with Linux environments, HPC cluster management tools, and knowledge of batch schedulers or MPI/OpenMP are often required. Strong problem-solving abilities, teamwork, and effective communication help you excel in collaborating with researchers and technical teams. These skills ensure efficient support and optimization of complex computing systems critical for scientific and technical advancements.

What is the difference between Entry Level High Performance Computing Engineer vs Entry Level Data Scientist?

AspectEntry Level High Performance Computing EngineerEntry Level Data Scientist
Required CredentialsBachelor's in Computer Science, Engineering, or related field; knowledge of parallel computingBachelor's in Data Science, Statistics, or related; programming skills in Python/R
Work EnvironmentResearch labs, tech companies, supercomputing centersBusiness, tech firms, research institutions
Industry UsageHigh-performance computing, scientific research, simulationsData analysis, machine learning, predictive modeling

Entry Level High Performance Computing Engineers focus on developing and optimizing computational systems for scientific and technical applications, while Entry Level Data Scientists analyze data to extract insights. Both roles require programming skills and a strong technical background, but they serve different industry needs and environments.

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 Entry Level High Performance Computing Engineer jobs in California?

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

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

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

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

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

Infographic showing various Entry Level High Performance Computing Engineer job openings in California as of September 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, 1% Temporary, and 2% Contract. Highlights an 84% Physical, 1% Hybrid, and 15% Remote job distribution.

Sr. ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs

Cupertino, CA • On-site

Amazon
IT Services • 10K+ employees

$128K - $177K/yr

Full-time

Re-posted 5 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,180 frontline employees who took The Breakroom Quiz


Job description

The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium.
The Acceleration Kernel Library team is at the forefront of maximizing performance for AWS's custom ML accelerators. Working at the hardware-software boundary, our engineers craft high-performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration.
The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators

This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance.
As part of the broader Neuron Compiler organization, our team works across multiple technology layers - from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology
This is an opportunity to work on cutting-edge products at the intersection of machine-learning, high-performance computing, and distributed architectures

You will architect and implement business-critical features, publish cutting-edge research, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint.

We're inventing. We're experimenting. It is a very unique learning culture.

The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators.
Explore the product and our history.
https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html
https://aws.amazon.com/machine-learning/neuron/
https://github.com/aws/aws-neuron-sdk
https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success
Key job responsibilities
Our kernel engineers collaborate across compiler, runtime, framework, and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software, hardware, and machine learning systems, you'll bring expertise in low-level optimization, system architecture, and ML model acceleration

In this role, you will:
* Design and implement high-performance compute kernels for ML operations, leveraging the Neuron architecture and programming models
* Analyze and optimize kernel-level performance across multiple generations of Neuron hardware
* Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks
* Implement compiler optimizations such as fusion, sharding, tiling, and scheduling
* Work directly with customers to enable and optimize their ML models on AWS accelerators
* Collaborate across teams to develop innovative kernel optimization techniques
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Inclusive Team Culture
Here at Amazon, we embrace our differences

We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.

Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment

We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.


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About Amazon

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Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US