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Systems Research Engineer, GPU Programming

Together AI· Research
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San Francisco$200k - $300kfull-timePosted 11mo ago

About the role

Systems Research Engineer specialized in GPU Programming focused on developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications, co-designing kernels and model architecture, and contributing to efficient GPU architectures and programming models.

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

Qualifications

  • Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, or equivalent practical experiences
  • 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

Skills

Required:GPU programmingML/AI knowledge

Benefits

  • health insurance
  • startup equity
  • other benefits
  • flexibility in terms of remote work
Last updated Sep 9, 2026. Interested? Apply on the company site.

About Together AI

The AI Acceleration Cloud - Fast Inference, Fine-Tuning & Training

Run and fine-tune generative AI models with simple APIs and scalable GPU clusters. Train & deploy at scale on The AI Acceleration Cloud.

AI native cloudFine-TuningGPU clustersInferenceTrainingai-infrastructure-and-developmentbrex-fastest-growing-2025liquid-ai-recruiting-target
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