[Hiring] Machine Learning Developer @860 Morgan Stanley Svcs Canada Co

Role Description

We're seeking someone to join our Trade Surveillance Analytics team as a Machine Learning Developer in Non-Financial Risk Technology to build robust data pipelines, scalable ML systems, and innovative analytics and collaborate with Data Scientists, Developers, and cross-functional stakeholders to transform big data into actionable insights—bringing high-impact analytics from concept to production.

This is a Software Engineering III position at Associate level, which is part of the job family responsible for developing and maintaining software solutions that support business needs.

What you’ll do in the role:

• Design, develop, and maintain data pipelines for ingesting, transforming, and analyzing large-scale trading datasets.
• Implement and productionize advanced analytics and machine learning workflows—leveraging Spark, Python and modern big data technologies.
• Collaborate closely with Data Scientists and Engineering team members to operationalize models and automation.
• Optimize code and data workflows for performance, scalability, and reliability.
• Leverage MLOps components, automate feature engineering as part of robust, production ML workflows.
• Write clean, well-tested, well-documented code and participate in code reviews.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field.
• 5+ years of relevant professional experience in software development, data engineering, or machine learning applications.
• Proficiency with Python (ex. Pandas, NumPy, Jupyter Notebooks), SQL for data engineering and analytics.
• Exposure and/or interest in the latest technologies in machine learning, AI (Modern AI: Generative AI, Multi-Agent Systems, MCP, Agentic AI architectures) and big data; advocate for best practices across the team.

Requirements

• Experience with Java, Scala (e.g. Spark)
• Big Data & ML Platforms: Spark, Databricks, Snowflake, Azure
• Machine Learning & MLOps: Feature stores, model registry, MLOps frameworks, continuous model monitoring and retraining, scalable model deployment
• Front-end Development: React (for building dashboards or UI integrations)

Benefits

• Hybrid work environment, combining remote work and attendance in the office.
• Knowledge of French and English is required.