IPC AI/ML Developer Intern (September 2026 - 12 Months - Toronto)

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

Design and build AI-driven, distributed platforms that enable real-time analytics, predictive intelligence, and autonomous operations across payments, supply chains, and simulation environments.

Key Responsibilities

• Develop ML models for prediction, anomaly detection, fraud, and optimization.
• Build real-time data pipelines for structured/unstructured data and low-latency decisioning.
• Design and operate AI-native distributed infrastructure across GPUs/CPUs and hybrid cloud.
• Integrate models into production systems, analytics platforms, and dashboards.
• Enable continuous training, monitoring, and retraining (MLOps/LLMOps).
• Support agentic simulations and scenario modeling for complex systems.
• Ensure security, privacy, and regulatory compliance.

This position resides in Toronto and is a 12-months work term commencing in September 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

Core Skills:- Machine Learning (regression, deep learning, NLP), Real-time data engineering, Distributed systems & Kubernetes, GPU/accelerator orchestration, MLOps/LLMOps, Secure & privacy-preserving compute.