Responsibilities

The Engineering Manager will lead, mentor, and manage a team of engineers focused on developing and optimizing ML model inference and performance. They will oversee technical strategy and architecture decisions, driving improvements across the engineering organization. Collaboration with cross-functional teams will be essential to ensure seamless integration and scalability of ML models in production environments. The manager will dive into the codebase of frameworks like TensorRT, PyTorch, and CUDA to identify and resolve complex performance bottlenecks. They will drive the development and deployment of large-scale optimization techniques for various ML models, particularly large language models (LLMs). Additionally, they will own the full lifecycle of projects from inception through delivery, including planning, execution, and resource management, while fostering a collaborative and inclusive team environment that encourages continuous learning and growth.