Senior MLOps Engineer

Jobber is seeking a Senior Machine Learning Operations Engineer to build an ML platform from the ground up. Reporting to the Director of Data, this role will focus on unlocking improved operational outcomes, workflow efficiencies, and new business insights across the organization. The ideal candidate will collaborate with Data Scientists and ML engineers to define project scopes, implement robust data pipelines, oversee the complete MLOps lifecycle, and establish best practices for ML model management.

Key responsibilities include:

• Architecting and building a comprehensive ML Platform
• Designing and implementing data pipelines for structured and unstructured data
• Conducting feasibility analyses and providing data-driven recommendations
• Implementing end-to-end MLOps pipelines for model training, evaluation, and deployment
• Establishing best practices for version control, testing, and monitoring of ML models
• Architecting scalable data processing systems for large-scale ML applications

Required skills:

• Strong background in software or data engineering
• Excellent communication skills
• Proficiency in Python programming
• Experience with Apache Spark, Docker, CI/CD technologies, and AWS services
• Expertise in building and maintaining complex ETL pipelines
• Proficiency with workflow management tools like Apache Airflow and dbt

Jobber offers a competitive compensation package, including extended health benefits, retirement savings plan matching, stock options, and a supportive work environment focused on personal and professional growth. The company has been recognized as a Top 10 Great Place to Work in Canada and is committed to fostering an inclusive and diverse workplace.