AI Engineer - Banking Domain
Contract AI engineer (12 months, renewable, hybrid) embedded in a major Canadian bank, building production ML and GenAI solutions for fraud, AML, credit risk, and customer analytics using Python, PyTorch/TensorFlow, MLOps tooling (MLflow, Kubeflow, Azure ML, SageMaker), and LLM/RAG stacks (OpenAI, LangChain) on Azure, AWS, or GCP.
- Compensation
- Not disclosed
- Location
- Montreal, Canada
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Contract
- Experience
- 3+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 7+ years in AI/ML engineering
- 3+ years in banking or financial services
- Advanced Python skills: PyTorch/TensorFlow, Scikit-learn, Pandas
- Hands-on MLOps experience: MLflow, Kubeflow, Azure ML, or SageMaker
- LLM/GenAI development: OpenAI, Azure OpenAI, LangChain, RAG architectures
- Cloud proficiency: Azure (preferred), AWS, or GCP
- Knowledge of OSFI E-23 model governance, PIPEDA, and explainable AI for audits
- Experience with SQL and distributed data platforms (Spark, Databricks, or Snowflake)
- Canadian work authorization
Nice to have
- Azure AI-102, AWS ML Specialty, or Google Professional ML Engineer certification
- Exposure to IFRS 9, Basel III, or Open Banking frameworks
- Experience with real-time ML inference (Kafka, Flink)
- Bilingual English/French (asset for Montreal)
- FRM or CFA designation as a complement to technical skills
Full description
Engagement
Contract — 12 months, renewable
Domain
Banking & Financial Services
Locations
Toronto, ON | Montreal, QC | Vancouver, BC | Calgary, AB
Work Model
Hybrid
Start
Immediate
ABOUT THE ROLE
We are looking for an experienced AI Engineer to design and deliver production-grade machine learning and generative AI solutions within a major Canadian bank. You will work across fraud detection, credit risk, regulatory compliance, and customer analytics, partnering with data, engineering, and compliance teams to bring AI from prototype to production.
KEY RESPONSIBILITIES
- Build and deploy ML and GenAI solutions for banking use cases (fraud, AML, credit scoring, customer analytics).
- Design LLM-based applications including RAG pipelines and document intelligence for internal workflows.
- Implement MLOps best practices: model versioning, CI/CD, monitoring, and drift detection.
- Ensure compliance with OSFI model risk guidelines, PIPEDA/CPPA, and internal governance frameworks.
- Communicate model performance and business impact to technical and non-technical stakeholders.
MUST-HAVE
- 7+ years in AI/ML engineering, with 3+ years in banking or financial services.
- Advanced Python skills: PyTorch/TensorFlow, Scikit-learn, Pandas.
- Hands-on MLOps experience: MLflow, Kubeflow, Azure ML, or SageMaker.
- LLM/GenAI development: OpenAI, Azure OpenAI, LangChain, RAG architectures.
- Cloud proficiency: Azure (preferred), AWS, or GCP.
- Knowledge of OSFI E-23 model governance, PIPEDA, and explainable AI for audits.
- Experience with SQL and distributed data platforms (Spark, Databricks, or Snowflake).
GOOD TO HAVE
- Azure AI-102, AWS ML Specialty, or Google Professional ML Engineer certification.
- Exposure to IFRS 9, Basel III, or Open Banking frameworks.
- Experience with real-time ML inference (Kafka, Flink).
- Bilingual English/French (asset for Montreal).
- FRM or CFA designation as a complement to technical skills.
HOW TO APPLY
Submit your resume, preferred location, and available start date. Canadian work authorization required.