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# Systems Research Engineer, GPU Programming

- **Company:** Together Ai
- **Location:** San Francisco, CA, United States (Remote available)
- **Salary:** $200,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Systems Engineering, Software Code Optimization, Profiling, Nvidia CUDA, Computer Programming, Systems Theories, Software Engineering, Software Systems, AI Infrastructure, Graphics Processing Unit (GPU), Parallel Computation, Gpu Programming, Information Technology
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/systems-research-engineer-gpu-programming-san-francisco-ca--806e8ee7-0cf8-44a3-b7d1-694340aabf21

## About the Role

GPU (Graphics Processing Unit), Systems Engineering, Research Skills, Algorithms, Programming Methodologies, Kernel Programming, Parallel Computing, GPU (Graphics Processing Unit), Artificial Intelligence (AI), Systems Engineering, * 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

## Description

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., * 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