Senior Member of Technical Staff, Web Data

Role Description

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 Common Crawl and other 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
• 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)

As a Senior Member of Technical Staff, Web Data, you will:

• 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.

Requirements

• Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

Benefits

• 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.
• 6 weeks of vacation (30 working days!).