Member of Technical Staff - Agent Code at Cohere

London, England, United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

PhD in Computer Science, Machine Learning, or a related field, with publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP)
Deep expertise in code LLMs and agent systems, with a strong understanding of the latest research and trends, including active contributions to their development
Hands-on experience with frontier LLMs and their applications in code generation or automation
Strong software engineering skills, with proficiency in Python and PyTorch, TensorFlow, or similar frameworks
Experience with distributed systems, cloud infrastructure, and scalable architectures
Proactive, self-motivated mindset, with a passion for solving ambitious, open-ended problems
Location alignment with ET to CET time zones for effective collaboration (hybrid or remote-friendly)

Responsibilities

Stay up-to-date with the latest research in code LLMs, agents, and related fields, implementing novel ideas into our systems
Design and implement scalable strategies to train code models, and deploy agent frameworks for inference and sampling
Collaborate with the pretraining team, create SFT trajectories, and work on existing and new RL algorithms
Hillclimb on existing benchmarks and design new ones that reflect the needs of our enterprise users
Lead experiments on our state-of-the-art compute infrastructure, pushing the boundaries of what’s possible with frontier LLMs

Skills

LLMs

Code Generation

Autonomous Agents

RAG

Semantic Search

Machine Learning

Research

Software Engineering

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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