LG AI Research
Research Scientist (LG AI Research Center, Ann Arbor)
Ann Arbor, Michigan, United States
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- Role family
- Data & ML
- Seniority
- Mid level
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 28 Sept 2026
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About LG AI Research Center, Ann Arbor
LG AI Research Center, Ann Arbor was established in March 2022 and tackles cutting-edge research questions to make the world a better place. Our mission is to develop impactful and responsible artificial intelligence that benefits technological innovations, scientific discovery, and all of humanity. We encourage open communication, collaboration, diverse perspectives, and a growth-mindset. We not only hire "well-established experts" in the relevant field of AI but also look for "high-potential candidates" who can ramp up quickly on topics aligned with our mission and values. We do not discriminate against our candidates on the basis of nationality, sex, age, religion, disability, or other legally protected statuses.
Responsibilities
Build and lead your own research agenda.
Develop new datasets, models, architectures, and algorithms in machine learning.
Collaborate on impactful research projects.
Publish scientific articles.
Demonstrate research outcomes to internal and external users.
Topics
Natural Language Understanding
Large language models
Reasoning
Dialog systems
Text generation (Conditional generation, Factual generation)
Curating and building large-scale high-quality datasets/benchmarks
Reinforcement learning
RL + Language
Compositional task generalization
Hierarchical reinforcement learning/planning/imitation learning
Meta/multi-task/transfer reinforcement learning
Offline reinforcement learning
Multimodal learning
Vision-language grounding
Video understanding
Deep generative models (images, videos, text, etc.)
Neural combinatorial optimization
Qualifications
Strong research/publication track record.
Expertise in state-of-the-art research topics and methods.
Proficiency with deep learning frameworks.
Nice to have Ph.D. degree with publications in major machine learning conferences.
Nice to have strong mathematical insights, large-scale modeling experience, dataset publications, and a desire to make breakthroughs.
Recruiting Process
Application Review → Coding Test → Technical Interview (Online) → Culture Fit Interview (Onsite)
The process is subject to change and we will contact you separately if you are selected to move forward with the recruiting process.
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