Senior Machine Learning Engineer at Itaú, driving innovation with data and AI solutions. Collaborating across teams to implement robust machine learning architectures and ensure scalable deployments.
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
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