IBM is a global leader in consulting and professional services, focused on technology transformation. The role involves working within a consulting team to develop and deploy machine learning solutions, while gaining hands-on experience with industry-leading data science technologies.
Join a fast-paced consulting team to conceptualize, develop and deploy machine learning solutions
Tackle difficult challenges faced by clients by combining subject matter expertise, data science, and technical execution
Learn and use industry leading data science technologies on a cloud platform
Work on innovative projects that generate value for external client engagements or internal initiatives
Qualification
Required
Demonstrated familiarity or interest in machine learning, statistical analysis, or data mining through previous internships, personal/academic projects, hackathons, and/or publications
Experience with one or more scripting languages (Python preferred), or a proven computer science foundation
Hands-on experience with GenAI/Agentic AI Frameworks (eg. Microsoft Agent Framework, langchain, semantic kernel, LangGraph, AutoGen, etc.) and LLM concepts (prompt-engineering, RAG, etc.)
Able to confidently communicate ideas to an audience of peers/managers, comfortable and effective in working independently and as a member of a cross-functional team
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
Bachelor's Degree
Minimum one work term in a data science or machine learning related role
Experience using machine-learning/data science libraries in python (scikit-learn, SciPy, pandas, TensorFlow, PyTorch)
General familiarity with databases and data-engineering tools (SQL, Spark)
Familiarity with cloud platforms (e.g. IBM, Cloud, Azure, AWS)
Benefits
IBM provides technology and consulting, including software, infrastructure systems, and cloud-based solutions.