Quantum AI Optimization Research Intern

IBM

Town of Yorktown (NY)

On-site

USD 89,000 - 164,000

Full time

4 days ago

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Job summary

IBM Research in Yorktown Heights is seeking a hands-on research intern to design, analyze, and benchmark quantum and hybrid quantum-classical algorithms for optimization and scientific computing. You will work with IBM Research scientists to explore AI-enabled algorithm discovery and quantum-centric supercomputing on real hardware and simulators.

The role emphasizes rigorous experimentation, reproducible code, and potential publication or open-source contributions.

Qualifications

Quantum computing knowledge with practical experience in implementing and running circuits (Qiskit).
Strong mathematical and algorithmic foundations: linear algebra, probability, discrete math, algorithm design.
Proficiency in Python and scientific libraries (NumPy, SciPy) with reproducible experiments.
Demonstrated research ability: framing problems, designing experiments, communicating results.
Depth in optimization, data-driven optimization, machine learning, or quantum optimization.

Responsibilities

Design, implement, and analyze quantum, classical, and hybrid quantum-classical optimization algorithms.
Develop and benchmark quantum optimization approaches on IBM quantum hardware and simulators.
Contribute to quantum-centric workflows and resource estimation analyses.
Establish performance baselines against classical solvers and document results.
Explore AI and agentic systems to accelerate algorithm discovery and workflow orchestration.
Implement research prototypes in Python (Qiskit ecosystem) with clean, reproducible code.
Present results in meetings and contribute to reports and open-source projects.