Cohere
Senior Member of Technical Staff, Synthetic Data
Toronto +4 · Remote · Staff · Full-time · Posted Nov 26, 2025
- Location
- Toronto
London
New York
Paris
Montreal
About the job
Build and improve synthetic-data pipelines and methods that transform large-scale web and code data to strengthen language-model training and performance.
What you'll do
- Design and build scalable inference pipelines for large GPU clusters; maintain and optimize synthetic-data pipelines.
- Analyze data quality through ablations and data-mixture experiments, and evaluate model performance.
- Research and implement synthetic-data curation methods in collaboration with researchers and engineers.
What they ask for
- Strong software engineering skills, Python proficiency, and experience building data pipelines.
- Familiarity with data-processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools.
- Experience with LLMs through work projects, open-source contributions, or personal experimentation.
- Familiarity with LLM inference frameworks such as vLLM and TensorRT; experience with large-scale datasets including web data, code data, and multilingual corpora.
Nice to have
- Paper at a top-tier venue, such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, or EMNLP.
Pay
CA$250K – CA$535K (ISO currency code: CAD; base salary or total pay not specified)
Tools
Python, Apache Spark, Apache Beam, Pandas, vLLM, TensorRT
AI focus
Develop synthetic data and data pipelines for language-model training, with data-quality analysis, ablations, and model evaluation.
Model-written summary · the original posting is authoritative