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 productive 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 strong 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