Senior Machine Learning Developer

Role Overview

Workplace

• The role is based in Toronto, Ontario, with a hybrid work arrangement.

Key Responsibilities

• Lead machine learning and AI initiatives from requirements definition through design, development, deployment, and production support.
• Coordinate complex projects across engineering, data, infrastructure, security, and platform teams.
• Design scalable, resilient, secure, and high-performing machine learning solutions aligned with enterprise architecture standards.
• Develop production-ready Python applications and machine learning services.
• Build, deploy, monitor, and optimize machine learning models in production.
• Drive MLOps practices including CI/CD, model lifecycle management, monitoring, automation, and observability.
• Manage risks, dependencies, technical challenges, project planning, estimation, troubleshooting, and root cause analysis.
• Evaluate emerging technologies and align solutions with security, compliance, governance, and operational requirements.

Required Technical Skills

• Advanced proficiency in Python application development and enterprise-grade applications, APIs, and machine learning services.
• Experience with machine learning libraries and frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, FastAPI, or equivalent technologies.
• Strong knowledge of AWS cloud-native services, including SageMaker, Lambda, API Gateway, S3, IAM, CloudWatch, EventBridge, ECS, and EKS.
• Knowledge of serverless, distributed, event-driven architectures, software design patterns, testing, and modern development practices.
• Experience developing, deploying, monitoring, and optimizing production machine learning models.
• Experience implementing MLOps, CI/CD pipelines, automation, model governance, observability, and operational excellence.

Qualifications

• At least 7 years of experience in software engineering, machine learning engineering, artificial intelligence, or a related technology discipline.
• Experience leading complex machine learning, AI, data, or cloud technology initiatives in enterprise environments.
• Experience translating business requirements into technical solutions, architecture designs, and implementation plans.
• Experience with Git, CI/CD pipelines, Agile delivery, APIs, microservices, distributed systems, and modern architecture patterns.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Preferred qualifications include Generative AI, LLMs, RAG, Kubernetes, platform engineering, AWS certifications, regulated-industry experience, or a related master's degree.

Compensation

• The listed salary range is $70,000.00 to $150,000.00.
• The pay type is salaried, and compensation may vary by location, skills, experience, education, and qualifications.
• Total compensation may include performance incentives, discretionary bonuses, and other benefits.

About BMO