Member of Technical Staff, Data Engineering
Member of Technical Staff, Data Engineering
Join to apply for the Member of Technical Staff, Data Engineering role at Cohere
Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who 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.
Why this role?As a Data Engineer specializing in pretraining data, you will play a pivotal role in developing the data pipeline that underpins Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of training data, including ingestion, cleaning, filtering, and optimization, as well as data modeling to ensure datasets are structured and formatted for optimal model performance. You will work with diverse data sources, such as web data, code data, and multilingual corpora, to ensure their quality, diversity, and reliability.
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.
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.
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 between EST and EU.
Responsibilities- Design and build scalable data pipelines to ingest, parse, filter, and optimize diverse web datasets.
- Conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance.
- Develop robust data modeling techniques to ensure datasets are structured and formatted for optimal training efficiency.
- Research and implement innovative 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.
- 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 like Common Crawl.
- 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).
Perks & 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!)
We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
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Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Engineering and Information Technology
Industries: Software Development
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