Member of Technical Staff, Pre-Training Data

Machine Learning Engineer Specializing in Pretraining Data

As a Machine Learning Engineer specializing in pretraining data, you will play a pivotal role in developing the data pipeline that underpins Cohere's advanced language models. In this role, you will conduct data ablations to evaluate data quality and construct pre-training data mixtures to enhance model performance. 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.

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 between EST and EU.

As a Member of Technical Staff, Pre-Training Data, you will:

• 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.

You may be a good fit if you have:

• Strong software engineering skills, with proficiency in Python and experience building data pipelines.
• Familiarity with curriculum learning, data mixing and data attribution.
• Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools.
• Experience working with large-scale datasets, including web data, code data, and multilingual corpora.
• 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).

• A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
• Full health and dental benefits, including a separate budget for mental health.
• RRSP matching, 401K, Pension Scheme.
• 100% Parental Leave top-up for up to 6 months, for either parent.
• Annual enrichment benefits:
  Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching.

• 6 weeks of paid vacation (30 working days!)
• Budget for traveling to other offices if you are remote, plus an annual company offsite.

• Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
• For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
• For those not near an office: a co-working benefit so you can work alongside others in your city.
• Everyone receives a $500 home office stipend to set up your workspace properly.

If any of the above doesn't line up exactly with your experience, we still encourage you to apply.

We 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.

We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.