Staff Research Engineer, Model Efficiency

Large Language Models (LLMs) continue to push the boundaries of what AI systems can do , but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including:

model architecture and MoE routing optimization

decoding and inference-time algorithm improvements

software/hardware co-design for GPU acceleration

performance optimization without compromising model quality

Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London.