Senior AI Training Systems Engineer

Genesis; Paris; Sur place; EUR 120 000 - 180 000; Plein temps

Résumé du poste

Genesis in Paris, France is seeking a senior ML infrastructure engineer to accelerate large-scale foundation model training by profiling and eliminating bottlenecks across the stack, from data pipelines to GPU kernels.

You will design, build, and optimize distributed training systems (PyTorch) for multi-node GPU clusters, focusing on scalability, robustness, and high utilization, with deep expertise in CUDA/cuDNN/Triton and production-grade Python.

Qualifications

• 8+ years in distributed systems, ML infra, or high-performance computing.
• Production-grade Python development experience.
• Expert in CUDA/cuDNN/Triton and kernel optimization.
• Experience with PyTorch training jobs using data, context, pipeline, and model parallelism.
• System-level mindset for hardware-software tuning and scaling.

Responsabilités

• Profile bottlenecks and reduce wall-clock time across the training stack.
• Design, build, and optimize distributed PyTorch training on multi-node GPU clusters.
• Implement low-level CUDA/CuDNN/Triton kernels and integrate into training frameworks.
• Develop monitoring and debugging tools for large-scale runs and regressions.
• Tune CPU/GPU balance, memory, data throughput, and networking for maximum utilization.

Connaissances

Python

PyTorch

CUDA/CuDNN

Distributed systems

Outils

CUDA

cuDNN

Triton

Description du poste

Genesis in Paris, France is seeking a senior ML infrastructure engineer to accelerate large-scale foundation model training by profiling and eliminating bottlenecks across the stack, from data pipelines to GPU kernels.

You will design, build, and optimize distributed training systems (PyTorch) for multi-node GPU clusters, focusing on scalability, robustness, and high utilization, with deep expertise in CUDA/cuDNN/Triton and production-grade Python.