As a Member of Technical Staff, Research Engineer (GPU Performance), you will be responsible for leading research and development of cutting-edge technologies that leverage the power of GPUs to accelerate machine learning workloads. You will work closely with our team to design, implement, and deploy innovative solutions that push the boundaries of what is possible with GPU-accelerated computing. You will be expected to stay up-to-date with the latest advancements in GPU technology and machine learning frameworks, and to apply this knowledge to drive the development of new products and features.
Key Responsibilities:
- Design and implement novel GPU-accelerated algorithms and data structures to improve the performance of machine learning workloads.
- Collaborate with cross-functional teams to integrate GPU-accelerated solutions into our products and services.
- Develop and maintain high-performance, scalable software systems that utilize GPU resources efficiently.
- Conduct research and experimentation to identify opportunities for GPU acceleration and develop new techniques to leverage GPU power.
- Stay current with the latest advancements in GPU technology and machine learning frameworks, and apply this knowledge to drive the development of new products and features.
Requirements:
- Ph.D. in Computer Science, Electrical Engineering, or a related field.
- 5+ years of experience in research and development of GPU-accelerated systems and machine learning algorithms.
- Strong background in computer architecture, operating systems, and software engineering.
- Experience with Python, C++, and/or other programming languages.
- Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.