Machine Learning Engineer

Crédit Agricole CIB; Singapore; Hybrid; SGD 80,000 - 120,000; Full time

Job summary

A prominent banking institution in Singapore seeks a seasoned Machine Learning Engineer to join their Digital Excellence Centre. The ideal candidate will have extensive experience in data science and applied ML, with responsibilities including deploying ML models and collaborating with cross-functional teams. Competitive remuneration is provided, and the role fosters innovative technology solutions.

Benefits

Competitive remuneration package

Focus on fair employment practices

Qualifications

• 6+ years of experience in data science and machine learning, with at least 3+ years in ML engineering roles.
• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Strong understanding of AI governance, model risk management, and regulatory requirements in AI.

Responsibilities

• Collaborate with data scientists and stakeholders to define ML solutions.
• Deploy ML models using MLOps practices.
• Build and maintain data pipelines for scalability.

Skills

Machine learning lifecycle

Python (pandas, scikit-learn, TensorFlow/PyTorch)

MLOps tools (MLflow, TFX, Airflow, Kubeflow)

NoSQL databases

CI/CD pipelines

Cloud platforms (GCP, AWS, Azure)

Data science techniques (supervised/unsupervised learning, NLP, time series)

Education

Master’s degree in AI / ML and data science

Tools

Docker

Kubernetes

Job description

Crédit Agricole Corporate and Investment Banking (Crédit Agricole CIB) is the corporate and investment banking arm of Crédit Agricole Group, world’s 10th largest bank by total assets.

Our Singapore center (“ISAP” or “Information Systems Asia Pacific”) is the 2nd largest IT setup (after Paris Head Office) for Crédit Agricole CIB's worldwide business. We work daily with international branches located in 30 markets by:

• Envisioning and preparing the Bank’s futures information systems
• Partnering and supporting core banking flagships and transverse areas in their large scale development projects
• Providing premium In-house Banking applications

This unique positioning empowers us to bring our core banking business a sustainable competitive advantage on the market.

We seek innovative and agile people sharing our mindset to support ambitious and forthcoming technological challenges.

Position

In a challenging and multicultural environment, we are looking for a Machine Learning /AI Engineer to join our Digital Excellence Centre (DEC) department of Crédit Agricole CIB. The department handles the development of transversal and international projects.

We are looking for a seasoned Machine Learning Engineer with a strong background in data science and applied ML, who can design, build, and deploy end-to-end machine learning solutions. This hybrid role requires a hands-on expert who can not only build models when needed but also engineer scalable, production-grade ML systems while adhering to the organization's AI governance and compliance standards.

Main responsibilities

• Collaborate with data scientists and business stakeholders to understand use cases and define ML solution; work on Proof of Concepts wherever needed
• Engineer and deploy ML models into production using MLOps best practices (model versioning, monitoring, CI/CD, etc.).
• Build & maintain data pipelines and model performance for scalability and maintainability.
• Ensure all models adhere to organizational AI policies, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and occasional model building where needed.
• Automate model retraining, testing, and monitoring to ensure performance over time.
• Document ML workflows, governance checkpoints, and risk assessments.
• Partner with DevOps, IT, and security teams to integrate solutions into enterprise platforms.

The position requires autonomy and reliability in performing duties while maintaining close communication with rest of stake-holders.

Qualifications and Profile

Mandatory:

• Have Master’s degree in the field of AI / ML and data science with proven ability to design and develop models
• 6+ years of experience in data science and machine learning, with at least 3+ years in ML engineering roles.
• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch, etc.).
• Strong knowledge in NoSQL databases (any experience in Graph database is desirable)
• Experience with MLOps tools: MLflow, TFX, Airflow, Kubeflow, or similar.
• Familiarity with cloud platforms (GCP, AWS, or Azure) for ML deployment.
• Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.
• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
• Strong understanding of AI governance, model risk management, and regulatory requirements in AI.
• Ability to communicate technical concepts to non-technical stakeholders.

Preferred skills:

• Experience with Responsible AI frameworks and bias/fairness testing.
• Exposure to feature stores, model registries, and data versioning.
• Knowledge of data privacy, anonymization, and compliance in regulated industries (e.g., banking, healthcare).

Other Professional Skills and Mind-set

• Ability and willingness to learn and adopt new technologies
• Strong organizational and communication skills
• Strong analytical and problem solving skills
• Awareness of various software development procedures
• Ability to follow defined procedures
• Understanding and respect of cultural diversity

We offer a competitive remuneration package, consistent with your qualifications and experience.

For fair employment practices, we are keen on Singaporeans. We offer a competitive remuneration package, consistent with qualifications and experience.

Interested applicants, please click on "APPLY"

Visit us on: http://www.ca-cib.com/