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Remote Gpu Programming Jobs in California (NOW HIRING)

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Your expertise in GPU computing, performance optimization, and parallel programming will be ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Your expertise in GPU computing, performance optimization, and parallel programming will be ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

iXsystems

Software Engineer III (AI)

Campbell, CA · On-site +1

$140K - $160K/yr

This is a remote position in the United States Base Pay Range The base pay range of this position ... Familiarity with GPU programming or GPU-accelerated libraries (CUDA, cuVS, DALI, TensorRT, or ...

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Remote Gpu Programming information

What are some common challenges faced by professionals in remote GPU programming roles, and how can they be addressed?

Remote GPU programming roles often involve unique challenges such as managing high-latency connections to remote servers, troubleshooting hardware-specific issues without physical access, and ensuring code compatibility across different GPU architectures. Effective communication with distributed teams is crucial, as is using robust remote debugging tools and version control systems. Staying proactive with documentation and regularly syncing with team members can help address these obstacles and support successful project delivery.

What is remote GPU programming?

Remote GPU programming refers to the practice of developing and running code that utilizes graphics processing units (GPUs) on computers or servers that are accessed over a network, rather than on your local machine. This approach allows developers to leverage powerful, often cloud-based, GPU resources to handle computationally intensive tasks like machine learning, scientific simulations, or rendering without needing specialized hardware themselves. It often involves using remote desktop tools, cloud platforms, or custom APIs to access and manage GPU resources remotely.

What are the key skills and qualifications needed to thrive as a Remote GPU Programmer, and why are they important?

To thrive as a Remote GPU Programmer, you need in-depth knowledge of parallel computing, proficiency in programming languages like C/C++, and experience with GPU architectures, often backed by a degree in computer science or a related field. Familiarity with technical tools such as CUDA, OpenCL, and GPU profiling/debugging systems is commonly required, along with certifications in GPU programming or high-performance computing. Strong problem-solving abilities, self-motivation, and effective remote communication skills help individuals excel in distributed teams. These competencies are crucial for efficiently developing and optimizing GPU-accelerated applications while collaborating across remote environments.
What are the most commonly searched types of Gpu Programming jobs in California? The most popular types of Gpu Programming jobs in California are:
What are popular job titles related to Remote Gpu Programming jobs in California? For Remote Gpu Programming jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Gpu Programming jobs in California look for? The top searched job categories for Remote Gpu Programming jobs in California are:
What cities in California are hiring for Remote Gpu Programming jobs? Cities in California with the most Remote Gpu Programming job openings:
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Infographic showing various Remote Gpu Programming job openings in California as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Systems Research Engineer, GPU Programming

Together AI

San Francisco, CA • On-site, Remote

$160K - $230K/yr

Other

Medical

Posted 5 days ago

Job description

About the Role

As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

Requirements
  • Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
  • Knowledge of ML/AI applications and models
  • Knowledge of performance profiling and optimization tools for GPU programming
  • Excellent problem-solving and analytical skills
  • Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences
Responsibilities
  • Optimize and fine-tune GPU code to achieve better performance and scalability
  • Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
  • Stay up-to-date with the latest advancements in GPU programming techniques and technologies
About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

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