Member of Technical Staff, Pre-Training Data

About Us

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products designed to solve real-world business problems. We train and deploy frontier models for enterprises building AI systems. Our work is instrumental to the widespread adoption of AI, and we are looking for individuals passionate about contributing to this mission.

Cohere is a global team of researchers, engineers, designers, and more, headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin, and Seoul.

About the Role

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. 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.

This role is remote-friendly with no location restrictions between EST and EU time zones.

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.

Requirements

• 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.

Nice to Have

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

Benefits

• A weekly lunch stipend of $75/£75 or equivalent in your local currency.
• Full health and dental benefits, including a separate budget for mental health.
• RRSP matching, 401K, or 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 remote, plus an annual company offsite.
• $500 home office stipend to set up your workspace.
• Co-working benefit for remote employees to work alongside others in their city.

How and Where We Work

Cohere is remote-friendly with offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin, and Seoul.

• For those in the office: Daily lunch program, plenty of snacks, and regular community and social events.
• For remote employees: Co-working benefits and a home office stipend.