Intern, Machine Learning Developer
Hybrid · Toronto, Ontario, Canada
Job Summary
Intern, Machine Learning Developer at Autodesk focused on building AI platform components and tools: contribute to core AI platform components including context/state SDKs, evaluation harnesses, and safety frameworks; design observability and logging tools to trace AI agent behavior, cost, and performance; develop data and model pipelines to support retrieval, prompt management, and memory systems; assist in creating guardrail and redaction APIs to ensure data safety and compliance in prompts/logs; collaborate with product AI teams to integrate platform services (context APIs, observability tools, evaluation frameworks) into active use cases; document findings, contribute to internal SDKs, and help define best practices for responsible and reproducible AI development; part of Autodesk’s Canada Intern Program (16 weeks, Sept 1–Dec 18 2026), with paid internship and Flexible Workplace supporting office, remote, and hybrid work preferences.
Required Qualifications
- Enrolled in a full-time undergraduate degree program with expected graduation in 2027 or later
- Major in Computer Science, Engineering, Data Science, Statistics, or related field
- Familiarity with Python and ML frameworks (e.g., Scikit-learn, PyTorch, TensorFlow)
- Familiarity with Data Engineering concepts such as data validation, ETL pipelines, and dataset versioning
- Understanding of Machine Learning lifecycle workflows, model evaluation, and experimental design
- Experience with Git and familiarity with cloud environments (e.g., AWS, Azure)
- Preferred: Exposure to LLMs, RAG architectures, or multi-agent systems
- Interest in building shared ML tools and SDKs for other developers
- Knowledge of semantic evaluation metrics and responsible AI practices
- Not specified if relocation; internship program notes flexible workplace
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