AI/ML CUDA Engineer

Avinya Technologies LLC
Sunnyvale, CA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence C++ (Programming Language) Nvidia CUDA Software Debugging Python (Programming Language) Tensorflow Software Engineering Pytorch Large Language Models Deep Learning Information Technology
+1 more
Embedded AI

Job description

We are seeking an experienced Embedded AI Engineer to join our team in validating PyTorch-based Large Language Models (LLMs) using CUDA SDK APIs. The successful candidate will be responsible for debugging, extending and replacing the underlying CUDA code to ensure seamless functionality on our company-specific AI processors., * Validate PyTorch-based LLMs on company-specific AI processors using CUDA SDK APIs

  • -Debug and troubleshoot issues related to CUDA code integration with PyTorch models
  • Extend and modify CUDA code to optimize performance on company-specific AI processors
  • Replace existing CUDA code with custom implementations to meet specific requirements
  • Collaborate with cross-functional teams to ensure successful integration of LLMs with company-specific AI processors
  • Develop and maintain validation frameworks and tools for PyTorch-based LLMs
  • Analyze and optimize the performance of LLMs on company-specific AI processors

Requirements

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering or related fields

  • Strong experience with CUDA programming and PyTorch framework
  • In-depth knowledge of deep learning models, particularly Large Language Models (LLMs)
  • Proficiency in C++ and Python programming languages
  • Experience with debugging and troubleshooting complex software issues.
  • Excellent problem-solving skills and attention to detail
  • Strong communication and collaboration skills

Nice to Have

  • Experience with AI processor architecture and design

  • Knowledge of other deep learning frameworks, such as TensorFlow

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