Senior Member of Technical Staff; Synthetic Data

Responsibilities

• As a Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models
• Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality
• You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality
• 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
• Design and build scalable inference pipelines that run on large GPU clusters
• Conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance
• Research and implement innovative synthetic 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

• Six weeks’ paid vacation
• Equity / stock options
• RRSP, 401(k), and Pension Scheme contributions
• Coverage for 100% of your insurance premiums across health, dental, vision, and travel
• Additional coverage for accessing mental health providers/services
• Six months of fully paid parental leave, including adoption and surrogacy
• Financial support for egg freezing and IVF in Canada and the UK
• A monthly fitness and wellness allowance
• Globally dispersed company that supports a remote work culture
• A $2,000 annual education benefit for professional development
• A weekly stipend for meals when working remotely and catered lunch when working from one of our global offices
• A monthly arts and culture allowance
• A monthly quality time allowance

• Strong software engineering skills, with proficiency in Python and experience building data pipelines
• A passion for bridging research and engineering to solve complex data‑related challenges in AI model training
• Experience working with LLMs through work projects, open‑source contributions or personal experimentation
• Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools
• Familiarity with LLM inference frameworks such as vLLM and TensorRT
• Experience working with large‑scale datasets, including web data, code data, and multilingual corpora

If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact

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

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!