Training Performance Engineer CUDA
Cohere
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 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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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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Reference: WJ-3875_16155666 · Posted 11 Nov 2026, 08:49 PM