[Remote] Member of Technical Staff, Model Efficiency at Cohere

New York, New York, United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

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

Responsibilities

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

Skills

Cohere

Provides NLP tools and LLMs via API

About Cohere

Cohere provides advanced Natural Language Processing (NLP) tools and Large Language Models (LLMs) through a user-friendly API. Their services cater to a wide range of clients, including businesses that want to improve their content generation, summarization, and search functions. Cohere's business model focuses on offering scalable and affordable generative AI tools, generating revenue by granting API access to pre-trained models that can handle tasks like text classification, sentiment analysis, and semantic search in multiple languages. The platform is customizable, enabling businesses to create smarter and faster solutions. With multilingual support, Cohere effectively addresses language barriers, making it suitable for international use.

Toronto, CanadaHeadquarters

2019Year Founded

$914.4MTotal Funding

SERIES_DCompany Stage

AI & Machine LearningIndustries

501-1,000Employees

Risks

Competitors like Google and Microsoft may overshadow Cohere with seamless enterprise system integration.

Reliance on Nvidia chips poses risks if supply chain issues arise or strategic focus shifts.

High cost of AI data center could strain financial resources if government funding is delayed.

Differentiation

Cohere's North platform outperforms Microsoft Copilot and Google Vertex AI in enterprise functions.

Rerank 3.5 model processes queries in over 100 languages, enhancing multilingual search capabilities.

Command R7B model excels in RAG, math, and coding, outperforming competitors like Google's Gemma.

Upsides

Cohere's AI data center project positions it as a key player in Canadian AI.

North platform offers secure AI deployment for regulated industries, enhancing privacy-focused enterprise solutions.

Cohere's multilingual support breaks language barriers, expanding its global market reach.

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