Optimize frontier language-model training with CUDA and Python at Cohere, working remotely or from offices aligned with ET to CET hours. Improve throughput and accelerator utilization across advanced AI systems.

As a Performance Engineer on Cohere’s Pre-Training team, you will optimize model and system performance. The work combines software engineering, machine learning, and low-level kernel development. You will identify bottlenecks, build profiling tools, and improve efficient language understanding and generation capabilities.

Key Responsibilities:

- Design scalable, high-performance software for model training
- Assess architectural choices affecting throughput and quality
- Write CUDA and Triton kernels for accelerators




- Research ideas across supercompute and data infrastructure
- Collaborate with researchers in the field

Requirements:
- Extremely robust software engineering skills
- Proficiency in Python, JAX, PyTorch, and XLA/MLIR
- Experience writing GPU kernels using CUDA or Triton
- Experience with large-scale distributed training strategies
- Familiarity with autoregressive models such as Transformers

Bring CUDA, distributed training, and machine-learning systems expertise to Cohere’s Pre-Training performance engineering work.

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📌 Training Performance Engineer Cuda (Quebec City)
🏢 Cohere
📍 Quebec City