We are seeking an experienced Machine Learning / AI Engineer to join a dynamic and multicultural team within a leading global financial institution at the forefront of digital transformation and innovation. This role involves designing, building, and deploying end-to-end machine learning solutions across international and cross-functional projects supporting strategic business functions across banking, finance, and risk domains. The ideal candidate will be hands-on in both model development and engineering scalable, production-grade ML systems, while ensuring alignment with AI governance and compliance standards. This is a fixed-term contract with client organisation. 
 

Mandatory Skill(s)

• Master’s degree in AI, Machine Learning, or Data Science;
• Must have 6+ years in data science and ML, including 3+ years in ML engineering lifecycle;
• Proficiency in Python and ML libraries (pandas, scikit-learn, TensorFlow/PyTorch);
• Must have experience with NoSQL databases; exposure to graph databases is a plus;
• Must have familiarity with MLOps tools such has MLflow, TFX, Airflow, Kubeflow;
• Must have cloud deployment experience such as AWS, GCP, or Azure;
• Strong grasp of supervised/unsupervised learning, NLP, time series analysis;
• CI/CD pipeline and containerization expertise (Docker, Kubernetes);
• Understanding of AI governance, model risk, and regulatory compliance and the ability to explain technical concepts to non-technical stakeholders;

Desirable Skill(s)

• Knowledge of Responsible AI frameworks and fairness/bias testing;
• Experience with feature stores, model registries, and data versioning;
• Familiarity with data privacy, anonymization, and compliance in regulated sectors.

Responsibilities

• Collaborate with data scientists and business teams to define ML solutions and build PoCs;
• Deploy and maintain ML models using MLOps best practices;
• Build scalable data pipelines and monitor model performance;
• Ensure models comply with internal AI policies and audit standards;
• Support feature engineering and occasional model development;
• Automate model retraining, testing, and performance tracking;
• Document workflows, governance checkpoints, and risk assessments;
• Work closely with DevOps, IT, and security teams to integrate ML solutions into enterprise platforms.

If you are interested in this role, click on the “Apply to this job” button below or you could also write in with your CV to Shilpi Gupta at Shilpi.G@sciente.com quoting the job title.