A career in IBM Consulting is rooted by long term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
About Business Unit:
IBM Consulting is IBM’s consulting and global professional services business, with market leading capabilities in business and technology transformation. With deep expertise in many industries, we offer strategy, experience, technology, and operations services to many of the most innovative and valuable companies in the world. Our people are focused on accelerating our clients’ businesses through the power of collaboration. We believe in the power of technology responsibly used to help people, partners and the planet.
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 an intern Machine Learning Developer, 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. Depending on the projects and team’s technical requirements, you will have the opportunity to work with technologies such as:
- Kubeflow, MLflow, Prometheus, Grafana
- Seldon Core, Spark, Kafka
- Pytorch, Tensorflow CUDA
- Computer Vision, Gen AI, LLM
This position is open to applicants who reside in Toronto or Montreal and is open to applicants seeking 4 month internship work terms, 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 the work term.
Candidates considered for a Quebec position must be fluent in French.
- 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
- 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