Staff Research Engineer, Model Efficiency

Job summary

Responsibilities

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.

• 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

What they're looking for

• Have a PhD in Machine Learning or a related field
• Understand LLM architecture, and how to optimize LLM inference given resource constraints
• Have significant experience with one or more techniques that enhance model efficiency
• Strong software engineering skills
• An appetite to work in a fast-paced high-ambiguity start-up environment