About the RoleAs 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.
Requirements- 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
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
CompensationWe offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
