AI-Augmented Optimization Research Intern
Visa Sponsorship
Relocation
AI Summary
Join Mitsubishi Electric Research Laboratories as an AI-Augmented Optimization Research Intern. This role involves working on a joint research project using LLMs and related technologies to aid in optimization problems. The ideal candidate will have a solid background in machine learning, linear algebra, and convex optimization.
Key Highlights
Joint research project on AI-augmented optimization
LLMs and related technologies
Operations Research optimization problems
Key Responsibilities
Work on a joint research project using LLMs and related technologies
Aid in the formulation, transformation, and accelerated solution of typical Operations Research optimization problems
Technical Skills Required
Benefits & Perks
$6,000-$8,000 monthly salary
Relocation stipend
Covered travel to and from MERL
Monthly Charlie Card for local commuting
Health insurance coverage after 90-day waiting period
Nice to Have
Experience with post-optimization enhancements, explanation, robustification, and generation of alternatives
Job Description
We seek a talented individual for a joint research project in AI-augmented optimization: Using LLMs and related technologies to aid in the formulation, transformation, and accelerated solution of typical Operations Research optimization problems. Depending on intern skill set, the project may also consider post-optimization enhancements ? explanation, robustification, and generation of alternatives. The ideal applicant will have technical background and research experience on both sides (AI & OR) of the project, including familiarity with software environments used to do machine learning & mathematical programming. The internship has flexible dates in 2026.
The Strongest Candidates Will Have
- A solid background in machine learning, linear algebra, convex optimization, algorithm analysis, computational geometry.
- Experience with Mixed-Integer Programs (linear, nonlinear, nonconvex)
- Experience deploying and fine-tuning LLM-type AI systems.
- Competence with related software packages such as Gurobi, CVX, PyOpt, PyTorch, etc.
- Fluency in python.
- Interest (& experience) in publishing in top-tier venues.
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MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERL?s employees to perform their job duties may result in discipline up to and including discharge.
Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.
In addition to base pay, interns receive a relocation stipend, covered travel to and from MERL, and a monthly Charlie Card for local commuting. Interns are invited to participate in weekly social gatherings and professional development opportunities, including research talks by both internal and external speakers. Interns who meet the 90-day waiting period are also eligible for health insurance coverage. MERL provides immigration support for qualified candidates as needed. Employment is considered ?at-will,? and the Company reserves the right to modify base salary or any other compensation program at any time, including for reasons related to individual performance, departmental or Company performance, and market conditions.
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