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.
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