Staff Research Engineer, Model Efficiency
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Intro
The Staff Research Engineer role at Cohere focuses on developing innovative solutions to boost the performance of Large Language Models (LLMs) inference by optimizing model efficiency. The team works on techniques such as model architecture optimization, efficient algorithms, and software/hardware co-optimization to address the challenges of computational and memory requirements in LLM deployment. The company values diversity, inclusivity, and a collaborative work environment. The role requires a PhD in Machine Learning or a related field, expertise in LLM architecture optimization, strong software engineering skills, and a passion for mentoring others. The position offers a remote-friendly environment with offices in Toronto, San Francisco, New York, and London, and provides various perks including health benefits, parental leave, personal enrichment benefits, and vacation time.
Tasks
- Develop innovative solutions to boost the performance of Large Language Model (LLM) inference
- Contribute to increasing the capabilities of models and the value they drive for customers
- Collaborate with a diverse team of researchers, engineers, and designers
Requirements
- PhD in Machine Learning or a related field
- Understanding of LLM architecture and optimization techniques
- Experience with enhancing model efficiency techniques
- Strong software engineering skills
- Published and presented at top-tier conferences (ICLR, ACL, NeurIPS)
- Passionate about mentoring others
- Ability to work in a fast-paced startup environment
Benefits
- Open and inclusive work culture
- Work on cutting-edge AI research
- Weekly lunch stipend
- Full health and dental benefits
- Parental Leave top-up
- Personal enrichment benefits
- Remote-flexible work environment
- 6 weeks of vacation
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