Kernel Engineer

About the Team: 

Our mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large scale optimization, active learning, among other topics.

The Research Platform team builds robust and scalable software to support our research efforts. It also offers core development services for mission critical goals and applications. In the Kernel team, we write Kernels for GPUs, we build a compiler to support important AI accelerators and we help with HW/SW co-design of future AI accelerators. 

About the Role: 

As a Research Engineer for GPU Kernels, you will write hi-performance kernels for the training and inference workloads. You will work with our internal and external customers to understand their needs and develop kernels that maximize performance. You will also work backwards from the capabilities of the GPUs to make model architectures amenable for efficient training and inference. If you are excited about maximizing HBM bandwidth, optimizing for instruction issue rate, shuffling within a warp, managing the precious register space and keeping the tensor cores at high utilization, this is the perfect opportunity!

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Develop high performance GPU kernels while paying close attention to utilization and application performance
• Make aggressive optimizations that overcome hardware limitations
• Develop low precision algorithms that deliver high performance with little loss of ML accuracy
• Work with ML engineers to develop model architectures that are amenable for efficient training and inference
• Work with our scaling team to deploy your kernels and manage our training uptime
• Work with hardware vendors and advise on HW/SW co-design   

You might thrive in this role if you:

• Are a strong coder with excellent skills in C/C++ and Python
• Have a deep understanding of GPU and/or other AI accelerators
• Have good experience with CUDA or a related accelerator programming language
• You have experience driving ML accuracy with low precision formats
• You are able to actively collaborate with infrastructure and ML engineers
• Have 3+ years of relevant industry experience
• Get a great deal of satisfaction with every percentage point in performance improvement

These attributes are nice to have

• PhD in Computer Science and Engineering with a specialization in Computer Architecture, Parallel Computing. Compilers or other Systems
• Participation in competitive programming competitions
• Experience building compilers
• Experience working with hardware developers

Benefits and Perks

• Medical, dental, and vision insurance for you and your family
• Mental health and wellness support
• 401(k) plan with 4% matching
• Unlimited time off and 18+ company holidays per year
• Paid parental leave (20 weeks) and family-planning support
• Annual learning & development stipend ($1,500 per year)