Machine Learning Developer Associate / Développeur(euse) en apprentissage automatique associé(e)

Introduction

A career in IBM Consulting is rooted by long term relationships and close collaboration with clients across the globe.

Introduction

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.

Your Role And Responsibilities

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 that solve enterprise-scale problems. As a team, we pride ourselves on tackling some of the most complex challenges our clients face by combining subject matter expertise, data science, and technical execution.

As a Machine Learning Developer Associate , you will have the opportunity to work with industry-leading machine learning technologies on cloud platforms such as IBM Cloud, Microsoft Azure, AWS, and edge environments. You will contribute to projects that deliver business value for client engagements and internal initiatives while collaborating with experienced practitioners across AI, software engineering, and consulting disciplines.

Depending on project requirements and business needs, you may work with technologies such as:

• GenAI and Agentic AI frameworks and models (AutoGen, LangGraph, vLLM, Microsoft Agent Framework, LLM)
• PyTorch, TensorFlow, CUDA
• Computer Vision technologies
• Machine Learning Operations (MLOps) and cloud-native AI solutions
• Spark, Kafka

In This Role, You Will

• Design, develop, test, and deploy machine learning and AI solutions for enterprise clients
• Support the development of GenAI, automation, and advanced analytics solutions
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
• Participate in model development, evaluation, deployment, and optimization activities
• Contribute to proof of concepts, prototypes, and production-ready AI applications
• Support project teams in delivering AI and machine learning solutions on major cloud platforms
• Continuously develop your technical and consulting skills through hands-on project experience, learning opportunities, and mentorship

Candidates considered for positions located in Quebec must be fluent in French.

This opportunity is based in Toronto, Calgary, or Montreal and supports Associate Consultant hiring cohorts commencing in May 2027 and September 2027. We are recruiting for both start dates and encourage eligible candidates to apply.

Successful applicants must have graduated from a recognized post-secondary institution prior to their employment start date. Please note that MBA and PhD graduates are not eligible for this program.

Required Technical And Professional Expertise

• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Mathematics, Statistics, or a related technical field
• Demonstrated familiarity or interest in machine learning, statistical analysis, artificial intelligence, or data mining through academic projects, internships, hackathons, research, publications, or personal projects
• Experience with one or more programming languages, preferably Python
• Hands-on experience with GenAI tools and frameworks (e.g., LangChain, Microsoft Agent Framework) and LLM concepts such as prompt engineering, RAG, and agentic workflows
• Strong analytical and problem-solving skills
• Ability to communicate technical concepts effectively to peers, managers, and clients
• Ability to work independently and collaboratively within cross-functional teams
• Must be eligible to work full-time in Canada

Preferred Technical And Professional Experience

• Internship, co-op, research, or project experience related to machine learning, computer vision, artificial intelligence, data science, or software engineering
• Experience using machine learning or data engineering frameworks such as Scikit-learn, PyTorch, TensorFlow, or PySpark
• Experience developing software prototypes, proof-of-concepts, or AI-driven applications
• Experience supporting projects involving AI, Machine Learning, Automation, GenAI, or Large Language Models
• Familiarity with cloud-native application development and related technologies such as Kubernetes, Docker, CI/CD pipelines, and distributed storage systems
• Experience with AI and cloud services on Microsoft Azure, AWS, Google Cloud Platform (GCP), or IBM Cloud
• Familiarity with MLOps concepts, model deployment, monitoring, and governance
• Experience working with data pipelines, ETL processes, or large-scale data platforms is an asset