Senior AI/ML Engineer

Scotiabank; Toronto; On-site; CAD 100,000 - 130,000; Full time

Job summary

Join Scotiabank's Global Wealth Management Technology team as a Senior AI/ML Engineer, applying your expertise to develop cutting-edge AI solutions. This role is pivotal in transforming financial services through innovation, ensuring security, and driving operational excellence. Collaborate with talented professionals in a supportive, inclusive environment that prioritizes continuous learning and growth.

Benefits

Performance bonus

Generous vacation

Health/medical/wellness benefits

Continuous learning environment

Employee banking privileges

Qualifications

• 5-7 years of experience in AI/ML solutions in production.
• Experience with data pipeline orchestration tools.
• Demonstrated experience mentoring junior engineers.

Responsibilities

• Lead the development and deployment of AI/ML models.
• Manage scalable ML pipelines and cloud-native infrastructure.
• Implement CI/CD processes for ML projects.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

XGBoost

MLOps

Cloud Platforms

Data Architecture

Tools

Airflow

Docker

Kubernetes

Azure ML

GCP

Job description

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Requisition ID: 226989

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

Overview:

We are seeking a seasoned and strategic Senior AI/ML Engineer to join our Global Wealth Management Technology (GWMT) team.

This role is ideal for a hands-on engineer with 5–7 years of experience in building scalable AI/ML systems, enabling production-grade workflows, and mentoring junior engineers. You will drive innovation at the intersection of financial data, cloud infrastructure, and advanced machine learning.

Why Join Us:

• Scotiabank’s Global Wealth Management (GWM) division is dedicated to delivering personalized financial advice, investment management, and estate planning solutions to clients globally.
• As part of this forward-thinking organization, you'll help develop intelligent, secure, and scalable platforms that elevate both client and advisor experiences.
• Your work will directly contribute to the next generation of wealth services through data-driven innovation and responsible AI practices.

Key Responsibilities:

• Lead the development, deployment, and monitoring of complex AI/ML models, including deep learning and natural language applications.
• Build and manage scalable ML pipelines using tools like Airflow, dbt, or Google Dataflow for both batch and streaming data workloads.
• Architect and optimize data workflows using modern data warehousing and lake technologies such as Databricks, BigQuery, Synapse, and Delta Lake.
• Design and operate real-time pipelines using Kafka, Pub/Sub, or similar event-streaming platforms.
• Implement and maintain robust CI/CD processes for ML using MLflow, Kubeflow, or equivalent orchestration tools.
• Develop and deploy models on cloud-native infrastructure using Azure ML, Vertex AI, Docker, and Kubernetes.
• Apply MLOps best practices for versioning, monitoring, retraining, and explainability.
• Mentor L7 engineers, support code reviews, and contribute to a collaborative engineering culture.
• Ensure secure model development, including encryption, RBAC, and compliance with GDPR, PIPEDA, and GLBA.
• Collaborate with data engineers, architects, and product teams to translate financial business problems into machine learning solutions.

Minimum Qualifications:

• 5–7 years of professional experience delivering AI/ML solutions in production environments.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and XGBoost.
• Experience building or contributing to at least one production-grade RAG pipeline, using vector databases such as Azure Cognitive Search, GCP Vertex AI Matching Engine, FAISS, or Pinecone.
• Hands-on experience with orchestration frameworks like LangChain, LlamaIndex, or Semantic Kernel for chaining context-aware agentic workflows.
• Proven experience with data pipeline orchestration and ML lifecycle tools (e.g., Airflow, MLflow, Kubeflow).
• Hands-on experience with cloud platforms (Azure, GCP) and container orchestration (Docker, Kubernetes).
• Strong understanding of data architecture concepts, including ETL, streaming, and warehouse modeling.
• Demonstrated experience mentoring junior engineers and leading technical initiatives.

Preferred Skills:

• Experience using managed vector search platforms like Azure AI Search and GCP Matching Engine in retrieval-augmented systems.
• Proficiency in Terraform, Pulumi, or Azure Resource Manager (ARM) for infrastructure automation.
• Familiarity with observability and monitoring stacks (Prometheus, Grafana, Azure Monitor, GCP Logging).
• Knowledge of model explainability frameworks such as SHAP, LIME, or counterfactual analysis tools.
• Prior exposure to financial services data, models, or regulatory environments is a bonus.

What’s In It for You

• You'll get to work with and learn from diverse industry leaders, who have hailed from top technology companies around the world.
• We foster an environment of innovation and continuous learning. We have an inclusive and collaborative working environment that encourages creativity, curiosity, and celebrates success!
• We provide employees with an environment that is safe, inclusive, and reflective of all communities by promoting fair and equitable treatment and prioritizing unconscious bias and anti-racism training.
• We offer a competitive total rewards package, including a performance bonus, company matching programs (pension & Employee Share Ownership), generous vacation; health/medical/wellness benefits; employee banking privileges.
• When in person collaboration is required, you can take advantage of our new state of the art ecosystems with a design focus on enabling collaboration through both environment and technology.

Location(s): Canada : Ontario : Toronto

Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.

At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here . Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.