GPU Kernels Engineer
Description For GPU Kernels Engineer
OpenAI is seeking a GPU Kernels Engineer to join our Research team in San Francisco. This role offers a unique opportunity to work on cutting-edge AI technology and contribute to the development of high-performance GPU kernels for machine learning workloads.
As a GPU Kernels Engineer at OpenAI, you will be responsible for optimizing and developing efficient GPU kernels to accelerate AI computations. You'll work closely with researchers and engineers to implement and optimize algorithms for large-scale machine learning models.
Key Responsibilities:
- Design and implement high-performance GPU kernels for machine learning operations
- Optimize existing kernels for better performance and efficiency
- Collaborate with researchers to translate novel AI algorithms into efficient GPU implementations
- Profile and analyze GPU code to identify bottlenecks and optimize performance
- Stay up-to-date with the latest advancements in GPU architecture and programming techniques
Ideal Qualifications:
- 5+ years of experience in GPU programming and optimization
- Strong expertise in CUDA, OpenCL, or other GPU programming frameworks
- Deep understanding of GPU architecture and parallel computing principles
- Experience optimizing machine learning workloads on GPUs
- Proficiency in C++ and Python
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow
- Strong problem-solving skills and attention to detail
- Excellent communication skills and ability to work in a collaborative environment
This role offers a competitive salary range of $240,000 to $440,000, along with generous equity and benefits. OpenAI provides a flexible work environment, with the option to work from our San Francisco HQ 3 days per week.
Join OpenAI and be at the forefront of AI innovation, working on challenging problems that have the potential to shape the future of artificial intelligence. If you're passionate about high-performance computing and want to make a significant impact in the field of AI, we encourage you to apply for this exciting opportunity.
Responsibilities For GPU Kernels Engineer
- Design and implement high-performance GPU kernels for machine learning operations
- Optimize existing kernels for better performance and efficiency
- Collaborate with researchers to translate novel AI algorithms into efficient GPU implementations
- Profile and analyze GPU code to identify bottlenecks and optimize performance
- Stay up-to-date with the latest advancements in GPU architecture and programming techniques
Requirements For GPU Kernels Engineer
- 5+ years of experience in GPU programming and optimization
- Strong expertise in CUDA, OpenCL, or other GPU programming frameworks
- Deep understanding of GPU architecture and parallel computing principles
- Experience optimizing machine learning workloads on GPUs
- Proficiency in C++ and Python
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow
- Strong problem-solving skills and attention to detail
- Excellent communication skills and ability to work in a collaborative environment
Benefits For GPU Kernels Engineer
- Medical, dental, and vision insurance for you and your family
- Mental health and wellness support
- 401(k) plan with 50% matching
- Unlimited time off and 13 company holidays per year
- Paid parental leave (20 weeks) and family-planning support
- Annual learning & development stipend ($1,500 per year)
