Cohere
AI Frontier · Enterprise LLMs
Cohere has 77 active AI-related job listings. The majority of these roles are focused on agents, representing 39% of the total. Engineering is the dominant function, with 60 positions. The company is actively hiring for roles related to model serving, agent orchestration, and fine-tuning. In the last 30 days, Cohere has posted 17 new AI roles, a significant increase compared to the previous 30-day period.
AI Frontier · Enterprise LLMs
Currently tracking 69 active AI roles, down 44% versus the prior 4 weeks. Primary focus: Agent · Engineering.
Cohere currently has 83 active AI-related roles in our index. The most common open titles are: Forward Deployed Engineer, Agentic Platform (2), Solutions Architect - Public Sector (2), Applied AI Engineer - Agentic Workflows (Singapore), Applied AI Engineer – Agentic Workflows, Applied AI Engineer – Agentic Workflows (Korea). Most positions are in Engineering and Research.
Cohere's active AI hiring is concentrated in: agents (36%), data (20%), serving infrastructure (17%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Cohere is hiring AI talent in: Canada (37 roles), United States (15 roles), United Kingdom (15 roles), France (3 roles).
Job postings at Cohere most frequently reference: model serving, agent orchestration, fine tuning, rag, inference infra.
In the past 30 days, Cohere has posted 12 new AI-related roles. That is a -33% change versus the prior 30 days (18 → 12).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Intern/Co-op (Fall, 2026) Cohere is seeking a Machine Learning Intern to design, train, and improve cutting-edge models, develop new techniques for training and serving models, train large-scale models on massive datasets, and explore continual and active learning strategies. The role involves working closely with product teams and learning from experienced staff. | Post-trainData | 9 |
| Research Internship (Fall / Winter 2026) Cohere is seeking Research Interns to collaborate on designing and implementing novel research ideas and shipping state-of-the-art models to production. Interns will conduct cutting-edge machine learning research, build and train large language models, and focus on expanding the frontier of knowledge in language modeling and related areas. Research results will be disseminated through publications, datasets, and code, contributing to practical applications in Cohere's product development. |
| PretrainPost-train |
| 9 |
| Manager of Technical Staff, Sovereign AI Manager of Technical Staff for Sovereign AI at Cohere, focusing on training and deploying frontier LLMs. The role involves leading a team of scientists and engineers, staying current with LLM research, and developing scalable strategies for training models. Requires a PhD, publication record, team management experience, and strong software engineering skills. | Pretrain | 9 |
| Research Engineer Cohere Labs is seeking Research Engineers to build experiments, debug models, scale training pipelines, and turn research ideas into working systems. This role involves implementing new methods, running large-scale experiments, and shaping research infrastructure, with a focus on deep learning frameworks, model optimization, and collaboration with scientists. | Post-trainAgent | 9 |
| Senior Research Scientist, Model Evaluation Cohere is seeking a Senior Research Scientist focused on Model Evaluation to create next-generation evaluation methods and infrastructure for LLMs. This role involves developing new benchmarks, advancing state-of-the-art evaluation techniques, and building scalable tools to measure LLM progress and capabilities. | Eval Gate | 9 |
| Senior Research Engineer, Model Evaluation This role focuses on developing and implementing next-generation evaluation methods and scalable infrastructure for measuring LLM progress. The Senior Research Engineer will create evaluation benchmarks, datasets, and environments, conduct research to advance LLM evaluation techniques, and build tools for analyzing evaluation results. The role requires a strong background in LLM evaluation, research, and software engineering. | Eval Gate | 9 |