AI Scientist/Engineer Intern (LG AI Research Center, Ann Arbor)

Job Application for AI Scientist/Engineer Intern (LG AI Research Center, Ann Arbor) at LG AI Research

AI Scientist/Engineer Intern (LG AI Research Center, Ann Arbor) Ann Arbor, Michigan, United States

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

Lead/contribute to impactful research projects.

Develop new datasets, models, architectures, and algorithms in machine learning.

Publish scientific articles.

Demonstrate research outcomes to internal and external users.

Topics

1. Natural Language Understanding

Large Language Models

Reasoning

Dialogue Systems

Text Generation (Conditional Generation & Factual Generation)

Curating and building large-scale high-quality datasets/benchmarks

2. Reinforcement Learning

RL + Language

Compositional task generalization

Hierarchical reinforcement learning/planning/imitation learning

Meta/multi-task/transfer reinforcement learning

Offline reinforcement learning

3. Multimodal learning

Vision-language grounding

Video understanding

Deep generative models (images, videos, text, etc.)

4. Neural combinatorial optimization

Qualifications

Motivation to lead/contribute to impactful research ideas.

Familiarity with state-of-the-art research topics and methods.

Proficiency in deep learning frameworks and strong programming skills.

Nice to have publications in major machine learning conferences.

Nice to have strong mathematical insights, large-scale modeling experience and a desire to make breakthroughs.

Recruiting Process

Application Review → Coding Test → Technical Interview (Online)

• 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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