Member of Technical Staff, Cohere

• Extremely strong software engineering skills
• Value test-driven development methods, clean code, and strive to reduce technical debts at all levels
• Proficiency in Python and related ML frameworks such as JAX, Pytorch and/or XLA/MLIR
• Experience using and debugging large-scale distributed training strategies (memory/speed profiling)
• [Bonus] Experience with distributed training infrastructures (Kubernetes) and associated frameworks (Ray)
• [Bonus] Hands-on experience with the post-training phase of model training, with a strong emphasis on scalability and performance
• [Bonus] Experience in ML, LLM and RL academic research

Desirable

• The integration team is responsible for developing and scaling machine learning algorithms and infrastructure for LLM post-training, with a focus on large-scale, distributed RL methods
• We strive for excellence in both engineering and science by meticulously designing experiments and design docs
• While tasks are assigned according to everyone’s expertise, there is a global team effort to write production code and support the team research efforts, depending on individual interests and organizational needs
• In particular, this role aims to enhance the global quality of the post-training codebase by implementing new tools to ease and support research, optimizing post-training algorithms, and scaling distributed RL to unprecedented levels
• Design and write high-performing and scalable software for training models
• Develop new tools to support and accelerate research and LLM training
• Coordinate with other engineering teams (Infrastructure, Efficiency, Serving) and the scientific teams (Agent, Multimodal, Multilingual, etc.) to create a strong and integrated post-training ecosystem
• Craft and implement techniques to improve performance and speed up our training cycles, both on SFT, offline preference, and the RL regime
• Research, implement, and experiment with ideas on our cluster and data infrastructure
• Collaborate, Collaborate, and Collaborate with other scientists, engineers, and teams!