Bachelor's degree or higher in Computer Science or a related field.

At least 7 years of professional experience in the software industry, with a minimum of 2 years in a tech lead role.

Proven experience with high-performance computing environments and distributed systems.

Demonstrated ability to scale ML training systems and optimize resource utilization.

Hands-on experience with job scheduling systems and managing cloud GPU environments (GCP, AWS, etc.).

Deep understanding of distributed computing concepts, including race conditions, memory optimization, and parallel processing.

Hands-on experience in ML model tuning for performance.

Experience with common ML training and inference tools including PyTorch, TensorRT, Triton, Accelerate, etc.

Strong analytical and problem-solving skills with the ability to troubleshoot complex system issues.

Excellent communication skills to collaborate effectively with cross-functional teams.

Experience with container orchestration tools (e.g., Kubernetes) and infrastructure-as-code frameworks.