Member of Technical Staff, Model Efficiency

Stack

Responsibilities

• ▹Improve core performance metrics by diving deep into model execution and identifying bottlenecks
• ▹Develop innovative optimizations
• ▹Collaborate closely with modeling and systems teams to experiment, measure, and ship improvements
• ▹Build expertise in advanced performance techniques: GPU/CUDA optimizations, kernel-level improvements, and execution strategies for MoE and large-scale architectures

Requirements

• ▹5+ years of experience writing high-performance, production-quality code
• ▹Strong programming skills in C++ or Python (Rust/Go also welcome)
• ▹Experience with large language models and the LLM inference ecosystem (e.g. vLLM, SGLang)
• ▹Ability to diagnose and resolve performance bottlenecks across the model execution stack
• ▹A strong bias for action — you ship fast, measure impact, and iterate

Nice to have

• ▹GPU programming, CUDA, or low-level systems optimization
• ▹Language modeling with transformers (MoE, speculative decoding, KV-cache optimizations)
• ▹Scaling performance-critical distributed systems (e.g. computation, search, storage)

Soft skills

What we offer

• ▹Weekly lunch stipend of about $75/£75 (or local equivalent)
• ▹Full health and dental benefits, with a separate mental health budget
• ▹RRSP matching, 401K, or pension scheme
• ▹100% parental leave top-up for up to 6 months, for either parent
• ▹Annual enrichment benefits: arts & culture, fitness/wellness, quality time, workspace improvement
• ▹Education & learning stipend for conferences, courses, and coaching
• ▹6 weeks (30 working days) of paid vacation
• ▹Budget for traveling to other offices, plus an annual company offsite
• ▹$500 home office stipend; co-working benefit for remote employees

About the company

Cohere is the leading security-first enterprise AI company, building cutting-edge foundation models and end-to-end products that solve real business problems. Co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris.