Staff Research Engineer, Model Efficiency

About the role

Cohere is a security‑first enterprise AI company building foundation models and end‑to‑end products. The Model Efficiency team tackles the inference bottleneck of large language models, delivering breakthroughs across the model execution stack.

Key responsibilities

• Explore and ship breakthroughs across the model execution stack, including model architecture and MoE routing optimization.
• Develop decoding and inference‑time algorithm improvements.
• Co‑design software and hardware for GPU acceleration.
• Optimize performance without compromising model quality.

Required profile

• PhD in Machine Learning or a related field.
• Deep understanding of LLM architecture and inference constraints.
• Significant experience with techniques that enhance model efficiency.
• Strong software engineering skills.
• Ability to thrive in a fast‑paced, high‑ambiguity environment.
• Publications at top‑tier conferences (ICLR, ACL, NeurIPS).
• Passion for mentoring others.

Required skills

• Machine Learning
• LLM inference optimization
• GPU acceleration

What we offer

• Weekly lunch stipend of $75 (or equivalent).
• Full health and dental benefits, including a mental‑health budget.
• Retirement savings matching (RRSP, 401k, pension).
• 100 % parental‑leave top‑up for up to 6 months.
• Annual enrichment benefits (arts, fitness, workspace credit).
• Education stipend for conferences, courses, coaching.
• 6 weeks paid vacation (30 working days).
• Travel budget for office visits and annual company off‑site.