This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
As a Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization.
Job Responsibility:
Design and build scalable inference pipelines that run on large GPU clusters
Conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance
Research and implement innovative synthetic data curation methods, leveraging Cohere’s infrastructure to drive advancements in natural language processing
Collaborate with cross-functional teams, including researchers and engineers, to ensure data pipelines meet the demands of cutting-edge language models
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 work projects, open-source contributions or personal experimentation
Familiarity with LLM inference frameworks such as vLLM and TensorRT
Experience working with large-scale datasets, including web data, code data, and multilingual corpora
A passion for bridging research and engineering to solve complex data-related challenges in AI model training
Nice to have:
Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP)
What we offer:
An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend