Our client is looking for a highly skilled Machine Learning Engineer to join their growing team in Mississauga. This role is ideal for a technically strong and experienced ML professional who thrives in a fast-paced, collaborative environment and is passionate about delivering scalable machine learning solutions on distributed systems such as Hadoop.
Key Responsibilities:

• Design, develop, and implement machine learning models using Spark ML for predictive analytics
• Build and optimize end-to-end training and inference pipelines on distributed platforms
• Process and analyze large datasets to uncover insights and engineer effective features
• Work closely with data engineers to integrate ML models into existing data pipelines
• Fine-tune models and hyperparameters to maximize performance and accuracy
• Develop scalable solutions for both real-time and batch inference
• Continuously monitor deployed models and address any performance issues
• Keep up-to-date with the latest tools, frameworks, and best practices in machine learning and distributed computing

Required Qualifications:

• 10+ years of experience as a Machine Learning Engineer or similar role
• Expertise in Apache Spark and Spark MLlib
• Solid understanding of predictive modeling techniques (e.g., regression, classification, clustering)
• Hands-on experience with distributed systems such as Hadoop
• Proficiency in Python, Scala, or Java
• Strong grasp of data preprocessing and feature engineering methodologies
• Familiarity with model evaluation metrics and production deployment practices
• In-depth knowledge of distributed computing and parallel processing principles

This office is located in Mississauga, and you will have to be 3 days onsite per week; must be onsite from Day 1