Research Engineer (LG AI Research Center, Ann Arbor)

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.

Responsibilities

• Build engineering-driven research ideas with self-motivation.
• Develop and collaborate on impactful research projects.
• Align, scale, and demonstrate our research products to internal and external users.
• Design new or improve state-of-the-art datasets, models, architectures, and algorithms in machine learning.
• Write scientific articles and contribute to our research track record.

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 programming skills and project portfolio.
• Strong proficiency in deep learning frameworks.
• Familiarity with state-of-the-art research topics and methods.
• Nice to have strong research/publication track record.
• Nice to have strong mathematical insights, large-scale modeling experience, dataset publications, and a desire to make breakthroughs.
• Nice to have experience in large-scale learning/parallelism, high-performance implementations, and user-interactive systems.
• Nice to have an advanced degree (e.g., M.S. or Ph.D.) with publications in major machine learning conferences.

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.