10 months ago
Responsibilities
- Design and build scalable inference pipelines running on large GPU clusters.
- Conduct data ablations to assess data quality and experiment with data mixtures to improve model performance.
- Research and implement synthetic data curation methods using Cohere’s infrastructure.
- Manage synthetic data end to end, including pipeline maintenance and optimization, data analysis and generation, and model evaluation.
- Collaborate with researchers and engineers to ensure data pipelines meet the needs of advanced language models.
- Transform web and code data with generative models to improve token efficiency and model quality.
Requirements
- Strong software engineering skills with proficiency in Python and experience building data pipelines.
- Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools.
- Experience working with LLMs through professional work, open-source contributions, or personal experimentation.
- Familiarity with LLM inference frameworks such as vLLM and TensorRT.
- Experience working with large-scale web data, code data, and multilingual corpora.
- Passion for combining research and engineering to solve complex data challenges in AI model training.
- A paper at a top-tier venue such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, or EMNLP is a bonus.
Benefits
- Open and inclusive culture and work environment.
- Weekly lunch stipend, in-office lunches, and snacks.
- Full health and dental benefits, including a separate mental health budget.
- 100% parental leave top-up for up to six months.
- Personal enrichment benefits for arts and culture, fitness and well-being, quality time, and workspace improvement.
- Remote-flexible work with offices in Toronto, New York, San Francisco, London, and Paris, plus a co-working stipend; applicants may be located between EST and EU.
- Six weeks of vacation, or 30 working days.
Tech Stack
Categories
Data EngineeringML Engineering
About Cohere
Cohere builds large language models and an enterprise AI platform that companies use for search, summarization, and workflow automation, delivered via API or private deployments. Founded in 2019 and headquartered in Toronto, it focuses on multilingual models, data controls, and options to run across major clouds or on-premises. The business is privately held and serves security- and compliance-sensitive organizations.