**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** This position is open to applicants who reside in Toronto or Montreal and is open to applicants seeking an 8 or 12 month internship work term, commencing in September 2025. 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 their work term. Our team is looking for candidates with exceptional technical aptitude, a passion for applied data science, and an interest in solving business challenges with machine learning. The successful candidate will join a fast-paced consulting team, composed of Partners, Product Managers, Data Scientists, Architects and Software Engineers to conceptualize, develop and deploy machine learning solutions to solve enterprise-scale problems. As a team, we pride ourselves on tackling some of the most difficult challenges our clients face by bringing together subject matter expertise, data science, and technical execution. As a Machine Learning Developer Intern - AIOps, you’ll have the unique opportunity to learn and use industry-leading ML technologies on a cloud platform (e.g. IBM Cloud, Azure, AWS or Edge) by working on a project that generates value for external client engagements or internal initiatives. Additional details include: * Develop and deploy machine learning models to enhance the operational efficiency and resilience of payments platforms * Implement predictive analytics and anomaly detection to identify and resolve issues proactively across the payments value chain * Build AI-driven solutions to optimize transaction routing, clearing, and settlement processes * Integrate machine learning models with observability tools like Splunk, Instana, or AppDynamics for enhanced monitoring and insight generation * Develop risk assessment algorithms to enhance the security and compliance of the payments system * Work with payments SRE teams to ensure seamless deployment and scaling of AIOps models * Align ML solutions with industry standards and regulatory compliance frameworks * Create data pipelines for processing real-time transactional and operational data from payments systems * Integrate AI solutions with payment orchestration and clearinghouse systems to improve end-to-end efficiency * Strong expertise in machine learning frameworks and AIOps platforms * Proficiency in programming languages and data processing tools * Hands-on experience with cloud-native platforms and containerization technologies * Experience with logging, monitoring, and observability tools * Proven experience in deploying ML models for anomaly detection, event correlation, and predictive analytics. * Hands-on knowledge of LLM-based systems and LLM observability/security * Experience with event correlation and supervised learning techniques Candidates considered for a Quebec position must be fluent in French. **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 **Preferred technical and professional experience** One or more work terms in a machine learning, computer vision or software engineering related role. Experience using machine-learning or data engineering libraries/frameworks in python (scikit-learn, Pytorch, TensorFlow, pyspark). Hands on R&D to develop software demos and prototypes. Support delivery project teams in areas such as AI, ML, Automation, LLM or Robotics on major cloud providers. Good familiarity with cloud application development and the tools required for building cloud-native data applications (Kubernetes, Docker, storage, etc.). IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.