Hybrid Senior Machine Learning Engineer

at Aviva

• Job title: Senior Machine Learning Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: $110,000 - $145,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Airflow, Apache, AWS, Azure, Cloud, Docker, EC2, Google Cloud Platform, Jenkins, Linux, Python, Scikit-Learn, Spark, SQL
• Location requirements: Hybrid, Toronto, Canada

About the role

• Senior Machine Learning Engineer designing and deploying scalable ML solutions at Aviva. Collaborating with teams to drive innovation in AI/ML platforms, ensuring reliable and efficient pipelines.

Responsibilities

• Design, develop, and deploy robust ML pipelines and services in production environments (cloud and on-prem).
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable ML solutions.
• Optimize model performance and ensure reliability, scalability, and maintainability of ML pipelines and systems.
• Implement MLOps best practices, including CI/CD, model versioning, monitoring, and retraining.
• Work with Snowflake and AWS services (e.g., S3, EC2, ECR, MWAA) to build and deploy ML models on the cloud.
• Develop and maintain end-to-end on-premise ML workflows solutions.
• Ensure data privacy, security, and compliance in all ML solutions.
• Mentor junior engineers and contribute to technical leadership within the team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 5+ years of experience in machine learning engineering or related roles.
• Strong proficiency in Python and ML libraries (e.g., scikit-learn, pyGAM, XGBoost).
• Hands-on experience with Snowflake, Snowpark, and Snowpark ML for data engineering and ML workflows.
• Deep understanding of AWS cloud services and infrastructure for ML deployment.
• Experience with Linux-based systems, including remote development via SSH.
• Proficiency in Jenkins for orchestration and automation of ML workflows.
• Experience with containerization (Docker).
• Strong proficiency in SQL, with the ability to optimize complex queries using query plans and performance tuning tools.
• Familiarity with data versioning tools (e.g., DVC, Feast), ML workflow tools (e.g., MLflow, Airflow), and monitoring frameworks.
• Excellent problem-solving skills and ability to work in a fast-paced environment.
• Would be an asset: Knowledge of feature stores and model registries.
• Experience with Apache Spark and Snowpark for scalable data processing.
• Exposure to other cloud platforms (e.g., Azure, GCP) is a plus.
• Contributions to open-source ML projects or publications.

Benefits

• Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.
• Outstanding Career Development opportunities.
• We’ll support your professional development education.
• Competitive vacation package with the option to purchase 5 extra days off per year.
• Employee driven programs focused on gender, LGBTQ+, origins, diversity and inclusion.
• Corporate wellness programs to support our employees’ physical and mental health.
• Hybrid flexible work model