Senior Engineer – Distributed Training Systems & Performance

• Location: Delhi NCR
• Exp - 4+ years

• Core Mandate: JAX/XLA/Pathways stack, sharding, FP8 numerics, checkpointing, MFU.

• Responsibilities:
• Optimize the core AI training infrastructure utilizing the JAX/XLA and Pathways stack.
• Design efficient tensor, pipeline, and data sharding strategies across massive TPU/GPU clusters.
• Implement FP8 numerics, architect reliable high-speed checkpointing systems, and continuously profile workloads to maximize Model FLOPs Utilization (MFU).

Requirements:

4+ years in distributed systems, High-Performance Computing (HPC), or ML infrastructure. Deep expertise in parallel computing, hardware accelerators, and low-level stack optimization