Research Intern — AI and Quantum Algorithms for Optimization 2027

IBM

Town of Yorktown (NY)

On-site

USD 89,000 - 164,000

Part time

44 hours ago

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Benefits offered by this job

8 paid holidays

IBM Employee Stock Purchase Plan

Job summary

IBM Research in Yorktown Heights seeks a 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 using Qiskit and Python to develop prototypes, perform rigorous experiments, and contribute to open-source projects.

This hands-on role emphasizes original technical work, with opportunities for publications and collaboration with IBM researchers on quantum-centric

Qualifications

Quantum computing knowledge and algorithms (circuit model, Hamiltonian simulation, variational & sampling-based methods).
Strong mathematical foundations: linear algebra, probability, discrete math, and computational complexity.
Proficiency in Python and scientific libraries (NumPy, SciPy) with reproducible coding practices.

Responsibilities

Design, implement, and analyze quantum, classical, and hybrid optimization algorithms.
Benchmark quantum optimization approaches on IBM quantum hardware and simulators.
Contribute to quantum-centric supercomputing workflows and performance baselines.

Education

Bachelor's Degree

Master's Degree

Tools

Qiskit

Python

NumPy

SciPy

JuMP

Pyomo

CVXPY

DOcplex

CPLEX

Gurobi

MOSEK

OR-Tools

Job description

At IBM Research, we build what's next in computing. Our teams work at the intersection of quantum information science, artificial intelligence, and high-performance computing — advancing quantum-centric supercomputing, where quantum processors and classical HPC resources work together to solve problems that neither can address alone.
As a research intern, you will join a team of scientists and engineers working on the algorithmic foundations of this vision: designing, analyzing, and benchmarking quantum and hybrid quantum-classical algorithms for optimization and scientific computing, and exploring how AI and agentic systems can accelerate algorithm discovery and workflow orchestration. You will have access to IBM's fleet of utility-scale quantum computers, the Qiskit software stack, and the classical computing infrastructure that surrounds them.This is a hands-on research role. Interns are expected to contribute original technical work, and strong outcomes frequently lead to publications at leading venues, open-source contributions, and continued collaboration with IBM Research.

Your role and responsibilities

You will work with IBM Research scientists on the design and analysis of algorithms for quantum and quantum-centric supercomputing, with a focus on optimization. Specifically, you will:

Design, implement, and analyze quantum, classical, and hybrid quantum-classical algorithms for optimization problems, including model-based (e.g. MILP, conic, nonlinear) and data-driven formulations.
Develop and benchmark quantum optimization approaches — variational and non-variational methods, quantum-enhanced heuristics, and circuit-cutting or sampling-based hybrid workflows — on IBM quantum hardware and simulators.
Contribute to quantum-centric supercomputing workflows that partition problems across QPUs and classical HPC resources, and characterize where quantum resources provide advantage.
Establish rigorous performance baselines against state-of-the-art classical solvers, and carry out complexity, scaling, and resource-estimation analyses.
Explore the use of AI and agentic systems for algorithm design, hyperparameter and ansatz search, code generation, and automated experiment orchestration.
Implement research prototypes in Python (Qiskit and the broader scientific Python ecosystem), with clean, reproducible, and well-documented code.
Present results in team meetings, contribute to technical reports, papers, and patent disclosures, and where appropriate contribute to open-source projects.

Required education

Bachelor's Degree

Preferred education

Master's Degree

Required technical and professional expertise

Quantum computing (required). Solid working knowledge of quantum information and quantum algorithms — circuit model, Hamiltonian simulation, variational and sampling-based algorithms, noise and error mitigation — with practical experience implementing and running circuits (e.g. Qiskit).
Strong mathematical and algorithmic foundations: linear algebra, probability, discrete mathematics and combinatorics, algorithm design and analysis, and computational complexity.
Programming proficiency in Python, including scientific and numerical libraries (NumPy, SciPy), plus the software discipline to produce reproducible experiments and readable, version-controlled code.
Demonstrated research ability: framing a problem precisely, designing and running rigorous experiments, and communicating results clearly in writing and in talks.
Depth in one or more of the following, in addition to quantum: model-based optimization (linear/integer/convex/nonlinear programming, metaheuristics); data-driven optimization and machine learning (including learning-to-optimize and surrogate models); quantum optimization; quantum-centric supercomputing and hybrid quantum-classical algorithm development; agentic AI and LLM-based systems; theory of computation.

Preferred technical and professional experience

Publications or preprints in quantum computing, optimization, theoretical computer science, or machine learning venues.
Hands-on experience running experiments on real quantum hardware, including transpilation, error mitigation and suppression, and interpreting hardware noise.
Experience with commercial or open-source optimization solvers (CPLEX, Gurobi, MOSEK, SCIP, OR-Tools) and modeling frameworks (JuMP, Pyomo, CVXPY, DOcplex).
Experience with HPC environments: distributed and parallel computing, GPU acceleration, job schedulers, and tensor-network or large-scale simulation tooling.
Experience building agentic AI systems — tool use, multi-agent orchestration, retrieval, and evaluation of LLM-driven workflows — particularly applied to scientific or mathematical problem solving.
Familiarity with quantum error correction, fault-tolerant algorithm design, or resource estimation.
Open-source contributions, especially to Qiskit or related quantum or optimization libraries.
Additional programming experience in C/C++, Julia, or Rust.
Fluency in written and spoken English.

ABOUT BUSINESS UNIT

IBM Research is the organic growth engine of IBM and an innovation engine for our customers and partners. As part of this mission, IBM Research anticipates and examines 'What's Next in Computing' to ultimately create and integrate the technologies the world relies upon to solve big challenges and unlock new opportunities. We create and pioneer new markets for IBM, our partners and customers as exemplified in our ongoing quest to reach practical and large-scale quantum computing. Across IBM Research, we realize the power and potential to accelerate discovery with our partners and clients by combining the power of high performance computing, AI, and Quantum, all integrated through the hybrid cloud.

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OTHER RELEVANT JOB DETAILS

Supplemental 1 employees may be eligible for up to 8 paid holidays, minimum of 56 hours paid sick time and the IBM Employee Stock Purchase Plan. IBM offers paid family medical leave and disability benefits to eligible employees where required by applicable law.
This position was posted on the date cited in the key job details section and is anticipated to remain posted for 15 days from this date or less if not needed to fill the role.
We consider qualified applicants with criminal histories, consistent with applicable law.

The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year.

Job Title

Research Intern — AI and Quantum Algorithms for Optimization 2027

Date posted

10-Sep-2026

Job ID

132434

City / Township / Village

Yorktown Heights

State / Province

New York

Country

United States