Intern Researcher
1 week ago
Huawei Canada has an immediate 8 month intern opening for a Researcher.
About the team:
The Intelligent Cloud Infrastructure Lab aims to innovate technologies, algorithms, systems, and platforms for next-generation cloud infrastructure. The lab addresses scalability, performance, and resource utilization challenges in existing cloud services while preparing for future challenges with appropriate technologies and architectures. Additionally, the lab aims to understand industry dynamics and technology trends to create a robust ecosystem.
About the job:
Keep up to date with AI-agent literature and proactively propose novel, impactful research ideas in self-evolving AI agents and MAS optimization.
Design and implement LLM-based agent architectures for planning, tool use, and decision-making.
Integrate agents with operations research and decision-making workflows (including forecasting, scenario planning, mathematical modeling, optimization solvers, simulation, and large-scale resource allocation).
Lead experiments at scale; analyze results; and publish at top AI venues (NeurIPS/ICML/ICLR/COLM/ACL/AAAI).
Collaborate effectively with a team of AI and OR researchers cross-functionally to transition research into prototypes and share findings via internal docs and talks.
The target annual compensation (based on 2080 hours per year) ranges from $78,000 to $150,000 depending on education, experience and demonstrated expertise.
Job requirementsAbout the ideal candidate:
PhD/MSc in CS/AI/OR/MATH/EE or a related field.
Demonstrated experience building AI agents (e.g., custom frameworks, LangChain/crewAI/Dify/MCP) and running LLM experiments end to end.
Strong ML/LLM background (prompting/finetuning, RAG/tool calling, RL or RLHF, evaluation design).
Solid Python + PyTorch skills.
Strong research appetite, with a track record of publications in top-tier AI/ML venues; patents a plus
Exposure to OR (combinatorial optimization, metaheuristics, MILP) and solvers (Pyomo/OR-Tools/Gurobi/HiGHS).
Experience running operations research or decision-making projects end-to-end, from problem formulation and data preparation to model development, solution implementation, and evaluation in real-world settings.
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