Drive innovation as a Machine Learning Data Engineer in Montreal, tackling challenges in training-data engineering for advanced AI models. Contribute to developing current pipelines and high-quality datasets. This unique position emphasizes developing new approaches to data curation and ensuring data quality at scale.

By leveraging your expertise in large-scale data processing, you will transform unstructured datasets into pivotal resources for training AI models. Collaborating with a team of AI researchers allows for both individual and collective advancements in machine learning. Key Responsibilities:

- Create pipelines to convert raw data into training datasets
- Process vast unstructured textual data efficiently




- Establish monitoring systems for data quality during training
- Build tools for data exploration and understanding
- Collaborate with stakeholders for evolving training needs

Requirements:

- Over 5 years in data infrastructure or related fields
- Strong skills in Python and distributed processing
- Experience with PII detection and content-safety measures
- Familiarity with workflows using Airflow or Dagster
- Knowledge of ML classifiers for data quality evaluation

Leverage your training-data expertise to impact the next generation of AI technologies.

📌 Machine Learning Data Engineer Focused on NLP (Montreal)
🏢 kadence
📍 Montreal