Senior Staff AI Performance Engineer, Crusoe Energy Systems

• If you are passionate about accelerating AI workloads, optimizing inference engines, and pushing the boundaries of high-performance computing, this role is for you
• Expertise in CUDA or OpenCL – Demonstrated experience developing CUDA kernels or equivalent technologies
• Proficiency in Python – Strong programming skills, particularly in Python, for AI and performance optimization tasks
• Experience with deep learning frameworks – Hands-on knowledge of training infrastructure such as PyTorch or TensorFlow
• Strong understanding of CPU & GPU architecture – Ability to analyze and optimize performance at the hardware level

Desirable

• As a Senior Staff AI Performance Engineer, you will play a pivotal role in optimizing scalable inference engines to enhance performance, efficiency, and speed
• Your contributions will directly impact Crusoe’s revenue model, as faster inference translates to greater token throughput and increased efficiency in our AI infrastructure
• Optimize inference engines – Improve inference performance in engines such as VLLM, ensuring maximum efficiency and scalability
• Enhance scalable AI infrastructure – Implement optimizations that accelerate AI inference, directly impacting Crusoe’s efficiency and revenue generation
• Develop CUDA kernels – Write and deploy CUDA kernels to optimize deep learning workloads, improving computational performance
• Conduct performance analysis – Profile and analyze training and inference workloads to identify and resolve bottlenecks
• Engage with the AI research community – Track developments in scalable inference, contribute to open-source projects, and publish research to advance the field
• Improve onboarding and documentation – Enhance internal documentation and tooling standards to streamline team workflows and training
• Collaborate cross-functionally – Work closely with AI researchers, engineers, and infrastructure teams to develop cutting-edge solutions