Senior AI Engineer

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

Job summary

A leading financial institution in Canada is seeking an experienced Senior AI Engineer to innovate financial data solutions through AI/ML. You will lead the development and deployment of scalable models, mentor junior engineers, and contribute to next-generation wealth services. Ideal candidates have 5–7 years of experience in AI solutions and proficiency in Python and ML libraries. A competitive rewards package is included.

Benefits

Competitive rewards package

Health benefits

Pension and shares

Vacation

Continuous learning opportunities

Qualifications

• 5–7 years of experience delivering AI/ML solutions in production environments.
• Experience with production-grade RAG pipelines using vector databases.
• Proven experience with data pipeline orchestration and ML lifecycle tools.

Responsibilities

• Lead development of AI/ML models and monitor deployment.
• Build scalable ML pipelines using various tools.
• Architect and optimize data workflows.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

XGBoost

MLflow

Kubeflow

Docker

Kubernetes

Tools

Airflow

Databricks

BigQuery

Synapse

Delta Lake

Kafka

Pub/Sub

Job description

Requisition ID: #

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

Overview:

We are seeking a seasoned and strategic Senior AI 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 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 division provides personalized financial advice, investment management, and estate planning solutions globally.
• Develop intelligent, secure, and scalable platforms to enhance client and advisor experiences.
• Contribute to next-generation wealth services through data-driven innovation and responsible AI practices.

Key Responsibilities:

• Lead development, deployment, and monitoring of complex AI/ML models, including deep learning and NLP applications.
• Build and manage scalable ML pipelines using tools like Airflow, dbt, or Google Dataflow.
• Architect and optimize data workflows with Databricks, BigQuery, Synapse, and Delta Lake.
• Design real-time pipelines using Kafka, Pub/Sub, or similar platforms.
• Implement CI/CD processes for ML using MLflow, Kubeflow, or similar tools.
• Deploy models on cloud infrastructure using Azure ML, Vertex AI, Docker, and Kubernetes.
• Apply MLOps best practices for versioning, monitoring, retraining, and explainability.
• Mentor engineers, support code reviews, and foster a collaborative culture.
• Ensure secure model development aligned with GDPR, PIPEDA, and GLBA standards.
• Collaborate with data engineers and product teams to translate business problems into ML solutions.

Minimum Qualifications:

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

Preferred Skills:

• Experience with managed vector search platforms like Azure AI Search and GCP Matching Engine.
• Proficiency in Terraform, Pulumi, or ARM for infrastructure automation.
• Knowledge of observability tools such as Prometheus, Grafana, Azure Monitor, GCP Logging.
• Experience with model explainability frameworks like SHAP, LIME, or counterfactual analysis.
• Familiarity with financial data, models, or regulatory environments is a bonus.

What’s In It for You:

• Work with industry leaders from top tech companies.
• Foster innovation and continuous learning in an inclusive environment.
• Benefit from fair treatment, unconscious bias and anti-racism training.
• Enjoy a competitive rewards package including bonuses, pension, shares, vacation, and health benefits.
• Utilize state-of-the-art collaboration environments when in person.

Location:

Canada: Ontario: Toronto

Scotiabank is committed to diversity and inclusion. If you require accommodations during the recruitment process, please inform our team. Only shortlisted candidates will be contacted. Thank you for your interest.