Member of Technical Staff, Pre-Training Data at Cohere (Toronto, Canada)Member of Technical Staff, Pre-Training Data

Who are we?

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.

We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.

We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!

Role Overview:

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.

Key Responsibilities:

• 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.

Qualifications:

• 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).

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.

FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:

• 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.