Cohere

Cohere is seeking a Machine Learning Engineer specializing in pretraining data to develop data pipelines for their advanced language models. The role involves conducting data ablations, evaluating data quality, and constructing pre-training data mixtures to enhance model performance, directly contributing to improvements in training metrics like throughput and accelerator utilization.

Cohere is seeking a Member of Technical Staff, Training Infra Engineer to design and write high-performant and scalable software for model training. This role will improve training setup, craft tools to speed up training cycles, and research/implement ideas on supercompute and data infrastructure. The ideal candidate has strong software engineering skills, proficiency in Python and ML frameworks like JAX/PyTorch, and experience with distributed training infrastructures and large-scale distributed training strategies.

Cohere is seeking a Data Engineer to work on foundational infrastructure for AI systems, including storage, product launches, and customer experiences. The role involves collaborating with researchers and engineers, running implementations end-to-end, and partnering across departments to define growth strategies. The ideal candidate has 5+ years of experience in production-grade data processing systems, strong Python and SQL skills, and experience with distributed data processing frameworks.

Cohere is seeking a Member of Technical Staff, Data Analysis and Evaluation, to ensure the quality, reliability, and performance of their LLMs. The role involves designing data collection tasks, evaluating dataset quality, analyzing model robustness and generalizability, and collaborating with cross-functional teams. Responsibilities include overseeing data collection, developing statistical methods for dataset evaluation, analyzing ML system generalizability, improving dataset quality and model performance, training LLMs, and conducting experiments.

Cohere is seeking a Machine Learning Engineer specializing in synthetic data to develop and manage the synthetic data pipeline for their advanced language models. This role involves end-to-end management of synthetic data, including pipeline optimization, data analysis and generation, and model evaluation. The engineer will work with diverse web and code data, transforming it using generative models to improve token efficiency and model quality, bridging research and engineering to enhance training metrics like throughput and accelerator utilization.

Software Engineer on the internal infrastructure team responsible for building and operating Kubernetes GPU superclusters across multiple clouds to support AI workloads for training foundational models. This role involves partnering with cloud providers, designing scalable systems, and ensuring stability and efficiency for research teams.

This role focuses on data annotation and evaluation for AI models, specifically breaking down engineering procedures into steps for the model to learn and complete. The specialist will task models, verify accuracy, and label/proofread outputs, requiring a background in engineering fields.