Ingénieur(e) MLOps senior

Job summary

Design, develop, deploy, and monitor machine learning and generative AI models, and build scalable MLOps/LLMOps infrastructure and APIs. Industrialize proofs of concept into production-ready solutions, document them, and hand them over to support teams.

Job details

Mission Being part of a dynamic team, you are convinced that technology can drive the transformation of our industry. In an agile oriented environment, you leverage the latest market leading technologies and solutions. Your actions will help our teams achieve our ambitious business goals by implementing a data centric enterprise architecture dedicated to Capital Markets. The position is located within our Global Markets IT department at the client. The Global Markets IT (GMI) department manages the global information system across the entire value chain of Global Markets businesses. The GMI teams are primarily located in Paris, London, New York, Montreal, Hong Kong, India, and Singapore. 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 Responsibilities 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 Requirements (ordered by priority) AWS – Hands on experience required; SageMaker experience is a strong asset. 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. CIB Environment – Prior experience in a Capital Markets or CIB context is a strong plus; familiarity with market finance specific challenges is valued. Tools and Methodologies: ML Model Lifecycle Model Registry CloudWatch Bedrock SQL Lambda Athena CodeBuild SageMaker AI S3 API Gateway MLflow Step Functions / Airflow EC2 Communication & Competencies Excellent written and oral communication skills Strong ability to explain technical issues to non technical audiences Rigorous incident and knowledge documentation habits Your future duties and responsibilities Required Qualifications To Be Successful In This Role Together, as owners, let’s turn meaningful insights into action. Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you’ll reach your full potential because… You are invited to be an owner from day 1 as we work together to bring our Dream to life. That’s why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company’s strategy and direction. Your work creates value. You’ll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise. You’ll shape your career by joining a company built to grow and last. You’ll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons. At CGI, we value the strength that diversity brings and are committed to fostering a workplace where everyone belongs. We collaborate with our clients to build more inclusive communities and empower all CGI partners to thrive. As an equal-opportunity employer, being able to perform your best during the recruitment process is important to us. If you require an accommodation, please inform your recruiter. That same commitment to fairness extends to how we use technology. To support our recruitment team, AI tools may be used to help assess applications though they never replace human judgement. All hiring decisions remain entirely in the hands of our recruitment professionals. To learn more about accessibility at CGI, contact us via email. Please note that this email is strictly for accessibility requests and cannot be used for application status inquiries. Come join our team—one of the largest IT and business consulting services firms in the world.

What you’ll do

Design, develop, deploy, and monitor machine learning and generative AI models, and build scalable MLOps/LLMOps infrastructure and APIs. Industrialize proofs of concept into production-ready solutions, document them, and hand them over to support teams.

Requirements

Requires senior-level Python expertise, hands-on AWS experience, and proven ability to deploy machine learning models to production; SageMaker experience is an asset. Candidates should have strong foundations in generative AI architectures and classical machine learning, experience collaborating with operations or MLOps teams, and ideally a Capital Markets or CIB background.

Listed skills

• SQL · Preferred
• REST APIs · Preferred
• CI/CD · Preferred
• Machine learning · Preferred
• Amazon Web Services · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• AWS
• Amazon SageMaker
• Python
• Machine Learning
• Generative AI
• MLOps
• LLMOps
• REST APIs
• gRPC
• Retrieval-Augmented Generation
• AI Agents
• ETL Pipelines
• CI/CD
• Model Deployment
• SQL
• Capital Markets

Job areas

• Technology
• Software
• Data & Analytics
• Finance & Accounting
• Consulting

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