Distributed ML/AI Infrastructure Engineer

About the role

We are looking for a Distributed ML Infrastructure Engineer to build and optimize the large-scale distributed training systems behind our foundation models. You will own the performance, scalability and reliability of training infrastructure spanning multi-node GPU and TPU clusters. This is a hands-on systems role at the core of how BrahmAI gets trained, working closely with

What you'll do

• Build and maintain distributed training infrastructure for large-scale AI workloads
• Optimize training performance through profiling, memory, communication and compute
• Implement distributed training strategies including data, tensor, pipeline and sequence
• Improve training throughput, scalability and reliability across multi-node clusters
• Develop automation, monitoring, profiling and debugging tools for production training

What you need

• 3–6 yrs of experience
• Machine learning
• Python
• PyTorch
• Shell scripting
• Linux
• Docker
• Any graduate

Good to have

• Kubernetes
• Git
• LLMs
• Physics