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Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises that are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build and each of us is responsible for contributing to increasing our models’ capabilities. We like to work hard and move fast to best serve our customers.
Cohere is a team of researchers, engineers, designers, and more, focused on building great products. Diversity of perspectives is required for success.
As a Machine Learning Engineer specializing in synthetic data, you will develop the synthetic data pipeline that is crucial to Cohere’s advanced language models. You will manage end-to-end synthetic data, maintain and optimize the pipeline, conduct data ablations and model evaluation to gauge data quality, and transform web and code data using generative models to improve token efficiency and model quality. You will bridge raw data and cutting‑edge AI models, contributing directly to improvements in throughput and accelerator utilization.
Bonus: paper at top‑tier venues (e.g., NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
We value and celebrate diversity and strive to create an inclusive work environment for all. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form.
We have offices in London, Paris, Toronto, San Francisco, and New York but also embrace remote work. No restrictions on where you can be located, within the EST and EU windows.