FY27 Research Intern GAD 🎓

The Simulation, Optimization and Systems (SOS) Group at Autodesk Research is looking for a passionate and skilled research intern for Summer 2026 at our Toronto office located in the MaRS Discovery District. You will be working with a small team to develop an agentic simulation setup workflow.

This position will involve developing an agentic workflow as an end-to-end simulation assistant that we are calling the sim-agent. The sim-agent will assist a user in all steps of the process of simulation for design. The tool should be capable of functioning mostly autonomously but will rely on some verification, alignment and definition of requirements from the user. You will be tasked with improving some existing agents, implementing some novel agents, modifying the overall workflow and testing/validating the sim-agent. This will involve working with VLMs, LLMs, ML and/or rule-based agents, all implemented using python.

Responsibilities:

• Develop agents of the following broad types:
  • VLM agents
  • LLM agents
  • ML agents
  • rule-based or heuristic-based agents
• Determine which type of agent is suited to a task
• Code in python to develop agents either from scratch or as improvements to existing agents
• Integrating simulation tools into the workflow
• Testing and validating individual agents and the overall workflow
• Document findings and results (potentially in the form of a publication)

Minimum Qualifications:

• Currently pursuing a PhD or Masters degree (Must be currently enrolled in a full-time, degree seeking program)
  • Mechanical engineering experience:
    • Design
    • Risk assessment/analysis
    • Running simulations
    • Validation through simulation
  • Experience in setting-up AI agents and agentic workflows
  • Experience working with LLMs (experience training or fine-tuning LLMs is a plus)
  • Experience working with VLMs (QWEN experience is a plus)
  • Experience with ML (geometric deep learning, graph neural networks)
  • Experience with writing/using MCP servers
  • Strong python experience

Preferred Qualifications:

• Experience with simulation tools such as SolidWorks, ANSYS, or Fusion is beneficial.
• Understanding of the Finite Element Method is an asset.
• Experience in reading/publishing papers
• Familiarity with AI technologies—including ML, VLMs, and agentic workflows—is valuable.