Über die RolleFDM is seeking an Intermediate ML Engineerlocated in
Markham to support a project in the
Insurance sector. Involvement in this project is anticipated to last initially
6 months to 12 months but may be extended.
This role will be
hybrid with requirements to be in office
3 days per week.
Das bringst du mitSenior ML Engineer (3/week in Markham):We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our AI/ML Platform team. The ideal candidate will have a strong background in designing, building, and deploying scalable machine learning solutions in both cloud and on-premise environments. Hands-on experience with Snowflake, AWS, and Linux-based systems is essential. You will collaborate closely with data scientists, data engineers, and product teams to operationalize ML models and drive innovation across the organization.
What You'll Do:- 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.
What You'll Bring:- 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.
Das erwartet dich 
