IBM Payments Centre Machine Learning Developer Intern (May 2026 - 8 months - Toronto)

**Introduction** We are seeking enthusiastic and driven interns to join our AI/ML and Advanced Analytics team. This internship offers an opportunity to work on cutting-edge projects involving machine learning, artificial intelligence, advanced analytics, and data science. You will gain hands-on experience developing and deploying AI-driven solutions for real-world applications in domains such as payments systems, advanced analytics, and edge AI hardware. **Your Role And Responsibilities**

- Develop and deploy advanced machine learning models for predictive analytics, anomaly detection, and optimization in business-critical systems, such as payments platforms and supply chains. - Design and implement analytical pipelines to process structured and unstructured data, supporting real-time decision-making and insights generation. - Build models for predictive maintenance, customer behavior analysis, fraud detection, and operational efficiency improvement. - Leverage advanced statistical methods and machine learning techniques (e.g., regression, classification, clustering, deep learning) to solve complex business problems. - Integrate ML models with analytics platforms and visualization tools for actionable insights delivery. - Collaborate with data engineers to ensure data pipelines are robust, scalable, and optimized for ML model training and deployment. - Monitor and retrain deployed models to ensure they meet performance and accuracy benchmarks over time. - Conduct exploratory data analysis (EDA) to uncover trends, correlations, and insights that inform strategic decision-making. - Apply natural language processing (NLP) techniques for text analytics, sentiment analysis, and document classification. - Ensure compliance with data privacy and security regulations in all analytics workflows.

This position resides in Toronto and is a 8 months work term commencing in May 2026. It is mandatory that all applicants are enrolled in full-time studies at a post-secondary institution and returning to full-time studies upon completion of the work-term. Please note that MBA and PHD Candidates are not eligible for this program. **Preferred Education** Bachelor's Degree **Required Technical And Professional Expertise**

- Proficiency in Python, R, or Java for AI/ML model development and testing - Strong data modeling skills, including the ability to design and implement normalized and denormalized schemas - Proficiency in encryption technologies and secure data handling, including experience with encryption protocols, data masking, and access control mechanisms - Experience with data integration tools and frameworks for real-time and batch data processing - Knowledge of cloud platforms and cloud-native database services, including serverless computing, data lakes, and containerized data workloads. - Strong troubleshooting skills to identify and resolve performance, integration, and data quality issues in complex data ecosystems - Ability to work effectively with cross-functional teams, ensuring that data solutions meet business and technical requirements - Familiarity with data governance practices, ensuring compliance with data privacy regulations and standards