Machine Learning Engineer II; B3617

Pay Details

$154,000 - $199,500 CAD

Toronto, Ontario, Canada

37.5 hours per week

Analytics, Insights, & Artificial Intelligence

The pay details posted reflect a temporary market premium specific to this role that is reassessed annually. TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience  compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role.

The base pay actually offered may vary based upon the candidate's skills and experience, job‑related knowledge, geographic location, and other specific business and organizational needs. As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

We are looking for experienced AI and ML Engineers who have worked under tight deadlines and on challenging tasks. The ideal candidate is a strong coder with solid AI and ML engineering experience. They should also have expertise in data engineering, machine learning system design and AI/MLOps.

• Gen AI:
  Develop and deploy scalable production Gen AI systems and applications.
• Predictive ML:
  Develop and deploy batch and real‑time model inference pipelines to production, perform end‑to‑end integration testing.
• Model Serving Framework:
  Develop in‑house model serving framework or integrate open‑source model serving framework with enterprise AI and data platform.
• ML System Design:
  Architect scalable machine learning and Gen AI systems that integrate with existing AI and data platforms and infrastructure, focusing on automation, operation efficiency, and reliability.
• Data Analysis & Processing:
  Perform data analysis, data preprocessing, and feature engineering on complex structured and unstructured datasets for machine learning models and AI applications.
• Model Deployment & Monitoring:
  Build and deploy model inference pipeline, ground truth pipeline, model monitoring pipeline to production environment. Continuously monitor production model performance and system performance.
• Automation:
  Build CI/CD pipelines to automate model deployment, deployment validation, model performance monitoring, and model retraining.
• Research:
  Stay up to date with the latest advancements in AI/ML technologies and apply them to improve existing ML systems or develop new systems and solutions.
• Technical Leadership:
  Provide technical expertise with a focus on efficiency, reliability, scalability, and security; includes planning, evaluating, recommending, designing, operationalizing, and supporting solutions in compliance with enterprise and industry standards.
• Collaboration:
  
  Work with AI/ML platform team, machine learning scientists, product owners and business partners to gather use case requirements and implement technical solutions for production AI/ML models and applications.

• Undergraduate degree required, advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science). Graduate's degree preferred with either progressive project work experience or…
• 1+ years experience of building machine learning production systems (includes post graduate experience)
• 2+ years of extensive programming experience
• Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models
• Solid experience with developing MLOps/AIOps CI/CD pipelines for deploying AI/ML models
• Solid experience with RAG, Agentic AI, LLM fine tuning, LLM serving, end‑to‑end GenAI application development, deployment, and production.
• Solid cloud experience with Azure or AWS and cloud AI/ML services such as Databricks, Kubernetes, Docker, and container orchestration, Azure Machine Learning, Azure Data Factory
• Strong experience with PySpark for big data processing and PyTorch for deep learning model serving
• Expert coder with Python, Java, or Scala
• Practical expertise in performance tuning, bottleneck…