Senior AI Training Infra Engineer - Distributed PyTorch

Genesis AI; Greater London; Hybrid; GBP 120,000 - 170,000; Full time

Job summary

Genesis AI seeks a senior ML infrastructure engineer to optimize distributed training pipelines and systems on multi-node GPU clusters in London. You will profile bottlenecks, implement low-level kernels, and integrate CUDA/cuDNN/Triton into high-level frameworks to maximize throughput and utilization.

The role requires deep expertise in distributed systems, Python, and PyTorch with a track record of hardware-aware optimizations across CPU/GPU boundaries and data movement.

Qualifications

• 8+ years of experience in distributed systems, ML infrastructure, or HPC.
• Production-grade Python experience.
• Low-level performance mastery with CUDA/cuDNN/Triton and kernel optimization.
• Experience scaling PyTorch training jobs with data, context, pipeline, and model parallelism.
• System-level mindset tuning hardware–software interactions for max utilization.

Responsibilities

• Profile and remove bottlenecks to reduce wall-clock convergence time.
• Design and optimize distributed training systems for multi-node GPU clusters.
• Implement low-level code (CUDA/cuDNN/Triton) and integrate into training frameworks.
• Optimize workloads for CPU/GPU balance, memory, data throughput, and networking.
• Develop monitoring and debugging tools for large-scale runs.

Skills

Distributed systems

Python

Performance optimization

PyTorch

Hardware-tuning

Tools

CUDA

cuDNN

Triton

Job description

Genesis AI seeks a senior ML infrastructure engineer to optimize distributed training pipelines and systems on multi-node GPU clusters in London. You will profile bottlenecks, implement low-level kernels, and integrate CUDA/cuDNN/Triton into high-level frameworks to maximize throughput and utilization.

The role requires deep expertise in distributed systems, Python, and PyTorch with a track record of hardware-aware optimizations across CPU/GPU boundaries and data movement.