MONTREAL [hybrid] - MLOps Engineer

About the Company:

As the founding entity of RAINBOW PARTNERS, Quanteam is a consulting firm specializing in Banking, Finance, and Financial Services. Guided by our core values of closeness, teamwork, diversity, and excellence, our team of 1,000 expert consultants, representing 35 different nationalities, collaborates across 10 international offices: Paris, Lyon, New York, Montreal, London, Brussels, Geneva, Lisbon, Porto and Casablanca.

We are looking for an MLOps Engineer for one of our clients, an investment bank set in Montreal

Role Overview :

The position is located within teams primarily located in Paris, London, New York, Montreal, Hong Kong, India, and Singapore. In an agile-oriented environment, the team is implementing a data-centric enterprise architecture dedicated to Capital Markets.

The client is looking to strengthen its team dedicated to AI projects for Capital Markets. The engagement will focus on new initiatives related to AI and Generative AI.

Key responsabilities :

AI / Generative AI Model Design & Development

• Data preparation, feature engineering, training, evaluation, versioning, deployment, and monitoring.
• Select the most appropriate models and techniques based on available data and project objectives.

MLOps / LLMOps Infrastructure

• Define and implement a robust MLOps architecture to support the full lifecycle of AI and Generative AI models, from design to production.
• Automate development, deployment, and monitoring processes for models.
• Ensure the quality, reliability, and scalability of models in production.

API Development & Python Engineering

• Design and develop REST and MCP APIs.
• Senior-level Python development across the full data and ML stack.

POC Industrialization

• Take internal proofs of concept through to production-grade solutions.
• Documentation and handover to Support.

Required Qualifications and Skills:

• AWS – hands-on experience required.
• API Development (REST / gRPC) – proven ability to deploy Machine Learning models to production.
• Generative AI Architecture (RAG / Agents) – solid foundations required; excellent command of classical Machine Learning is essential.
• Senior Python Development – deep expertise in Python for building ETL pipelines, database interactions, S3, orchestration, versioning, and CI/CD on the cloud.
• ML / Generative AI Model Knowledge – strong understanding of ML and GenAI models and their real-world applications.
• Cross-functional Collaboration – experience working alongside Ops or MLOps profiles.
• Tools and Methodologies: ML Model Lifecycle, Model Registry, CloudWatch, Bedrock, SQL, Lambda, Athena, CodeBuild, SageMaker AI, S3, API Gateway, MLflow, Step Functions / Airflow, EC2.

Competencies:

• Excellent written and oral communication skills.
• Strong ability to explain technical issues to non-technical audiences.
• Rigorous incident and knowledge documentation habits.

Nice to Have

• SageMaker experience is a strong asset.
• Prior experience in a Capital Markets or CIB context is a strong plus; familiarity with market finance-specific challenges is valued.