Senior Manager of Engineering (AI Inference)

Join Crusoe, a company focused on advancing AI strategies and making a meaningful impact in the world. As a Senior Manager of Engineering, you will lead a team dedicated to optimizing large language models for production. This role combines team leadership, technical direction, and hands-on coding, with a customer-facing aspect that ensures performance gains deliver clear business and customer value.

• Lead an engineering team focused on optimizing large language models for production, balancing team leadership with hands-on technical work.
• Collaborate with customer engineering teams to tailor deployments to their needs, ensuring performance gains deliver clear business and customer value.
• Drive the delivery of projects from early experiments to production optimizations, establishing performance goals and partnering with product and engineering leaders.

• A working knowledge of AI/ML pipelines and the full path of developing and deploying ML models
• A Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field
• Strong communication skills, particularly when explaining hard technical topics to customers and teammates
• Familiarity with methods for optimizing LLMs for high throughput / low latency inference
• Strong technical, hands-on experience in software engineering, low-level optimization, or ML infrastructure, with a continued desire to stay close to code and architecture
• Clear interest and hands-on experience with large language models
• A firm grasp of how GPUs are built and how they behave
• 2+ years of experience directly managing and leading an engineering team in a high-performance or ML-focused environment
• Hands-on experience shipping code in production with one or more general-purpose languages, such as Python or C++, with a strong preference for Python
• Comfort with modern LLM serving frameworks such as vLLM or SGLang, and with profiling and analyzing performance down to the kernel level
• A track record of making software systems run faster, especially for large language models
• Experience with CUDA or comparable technologies
• A strong command of software engineering fundamentals, with a record of building and shipping AI/ML inference systems
• Experience with Docker and Kubernetes
• Prior work building or tuning AI/ML projects, particularly in a customer-facing setting