Role Overview
As a Senior Member of Technical Staff specializing in web data for pre-training, you will play a pivotal role in developing the large scale web data pipeline that underpins Cohere’s advanced language models. In this role, you will work extensively with large-scale web corpora, transforming raw, noisy internet data into high-quality training data for pretraining. You will own key components of the data pipeline, including extraction, parsing, deduplication, and filtering. You will also analyze the composition and quality of web data, study its impact on downstream model performance, and collaborate closely with the broader data and evaluation teams to iterate on the training corpus.
Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact.
Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role. (EST/EU)
Key Responsibilities
Maintain large-scale pipelines for processing web corpora.
Work on filtering and quality-scoring systems to identify high-value web documents.
Analyze web data composition across domains, languages and time periods.
Develop and maintain highly-performant deduplication pipelines.
Collaborate with cross-functional teams, including researchers and engineers, to ensure data pipelines meet the demands of cutting-edge language models.
Qualifications
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 large-scale web datasets.
Knowledge of data quality assessment techniques and experimentation with data mixtures.
A passion for bridging research and engineering to solve complex data-related challenges in AI model training.
Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!
Working Location
This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.