입사지원자 개인정보 수집·이용 및 제공 동의서

LG AI연구원(이하 “연구원”)은 입사지원자의 개인정보 수집·이용, 업무 위탁에 관한 내용을 관계 법령에 따라 아래와 같이 고지하오니 동의해 주시기 바랍니다.

개인정보의 수집 및 이용

  • 개인정보 수집 항목
    • 필수 : 성명(한글/영문), 연락처(휴대폰 번호), 이메일 주소
    • 선택 : 학력사항, 경력사항, 어학 등 자격 사항, 주소, 병역사항, 채용 프로세스상에서 생성된 정보
  • 개인정보 수집 및 이용 목적
    • 채용 적합성 판단 및 서류 심사/면접의 근거 자료, 인재풀 활용
  • 개인정보 보유 및 이용 기간
    • 채용 지원자 정보는 입사 지원일로부터 3년간 보관합니다. 다만, 입사지원자가 개인정보의 삭제를 요청하는 경우에는 지체 없이 해당 개인정보를 삭제합니다.
    • ※ 입사지원자는 개인정보 수집 및 이용과 관련하여 동의를 거부할 권리가 있으나, 동의 거부 시 회사는 공정한 채용을 진행할 수 없기 때문에 지원에 제약사항이 발생할 수 있습니다.

■ 개인정보 취급업무 위탁 고지사항

수탁업체

업무 내용

제공하는 개인정보 항목

보유 및 이용 기간

Greenhouse Software, Inc.

채용 홈페이지 운영

이력서 포함 입사 지원시 제출한 개인 정보

지원일로부터 3년

■ 채용 서류 반환

  • 채용절차의 공정화에 관한 법률(채용절차법)" 제11조에 따라, 최종 합격자를 제외한 지원자의 경우 채용 사이트 및 전자우편으로 제출한 채용 서류를 반환받을 수 있습니다.
  • 최종 전형이 종료된 시점으로부터 180일 이내 채용 서류 반환 청구에 관한 내용을 careers@lgresearch.ai 로 요청하시면 14일 이내 반환해 드립니다.

LG AI연구원에 제출하신 정보는 채용을 위한 검증 목적으로만 이용되며, 그 이외의 목적으로는 이용되지 않습니다.

Research Engineer (Global AI Center, Ann Arbor)

About Global AI Center, Ann Arbor

The Global AI Center in Ann Arbor, inaugurated in March 2022, focuses on cutting-edge AI research with the goal of developing impactful and responsible AI, with a mission to propel technological innovations, advance scientific discovery, and benefit all of humanity at large. We foster an environment that encourages open communication, collaboration, diverse perspectives, and a growth mindset. Whether you are a well-established expert or a high-potential candidate eager to dive into topics that resonate with our mission, we welcome your contribution to our team. We seek individuals who are excellent not just in technical ability, but in their alignment with our values and the meaningful impact of their work. If you are driven by making a difference and desire your work to resonate beyond academic publications, join us in shaping the future of AI.

The ideal candidate for this role is someone who not only excels in research engineering but also thrives in a team setting, eagerly engages with cross-functional groups, and seeks to contribute to a shared vision. We look for individuals whose ambitions are matched by their drive to make a lasting difference through their work. If you have a track record of moving beyond theory to drive real-world advancements in AI, we would be excited to welcome you to our team. We do not discriminate against candidates based on nationality, sex, age, religion, disability, or other legally protected statuses.
 

Responsibilities

  • Develop and implement engineering-driven research ideas with a high degree of autonomy and initiative, ensuring these ideas are both innovative and practical.
  • Align research efforts with the needs of both internal and external users, ensuring that research products are scalable and demonstrate practical utility in varied applications.
  • Collaborate on impactful research projects that address complex, real-world problems, focusing on delivering tangible results.
  • Contribute to creating demos or systems that highlight the team's research and engineering efforts, demonstrating our AI innovations' practical applications and real-world effectiveness while fostering interdisciplinary collaboration with other teams.
  • Innovate and improve state-of-the-art models, datasets, architectures, and algorithms within machine learning.
  • (optional) Publish in top-tier conferences and journals and effectively communicate our AI research findings to both experts and broader audiences.

 

Focus Areas
Currently, we have two focus areas in research:

1. Develop AI agents capable of helping human users by solving tasks in complex environments, harnessing the latest advances in foundational models (such as large language models and large multimodal models), sequential decision-making, reinforcement learning, and multimodal AI.

2. Advance research and development of foundation models (e.g., large language models, multimodal foundation models, etc.) by developing compute-efficient training algorithms and architectures, constructing large-scale, high-quality datasets automatically, and improving generalization and adaptability with transfer learning and few-shot/zero-shot learning.

Some relevant research topics are listed below (but not limited to):

1. Natural Language Understanding
- Large Language Models
- Compute-efficient training algorithms and architectures
- Curating and building large-scale high-quality datasets/benchmarks automatically
- Improving instruction following and text generation via advanced instruction tuning and RLHF
- Reasoning
- Code generation
- LLM Agents
- Dialogue Systems

2. Reinforcement Learning
- RL + Language
- LLM Agents
- Compositional task generalization
- AI agents/assistants for real-world applications
- Hierarchical reinforcement learning/planning/imitation learning
- Meta/multi-task/transfer reinforcement learning
- Reinforcement learning from human feedback (RLHF)
- Offline reinforcement learning

3. Multimodal learning
- Vision-language grounding
- Video understanding
- Deep generative models (images, videos, text, etc.)

 

Minimum Qualifications

  • Strong programming skills and an impressive project portfolio, with a focus on producing work that has real-world applicability.
  • Proficient in the use of deep learning frameworks, with strong skills in applying these tools to solve complex problems.
  • Expertise in state-of-the-art AI research topics and methodologies, demonstrating a thorough understanding of the field's current landscape and its future potential.
  • Excellent communication skills, proficient at clearly presenting the research vision, technical concepts and methodologies, experimental results, and key insights to a diverse audience, with the ability to tailor the message for varying purposes and levels of technical expertise.

 

Preferred Qualifications

  • Extensive industry experience in applying AI research in a practical, product-oriented environment, with a focus on deliverable outcomes and real-world problem-solving.
  • Experience in large-scale learning, parallelism, high-performance implementations, large-scale model development, and interactive systems.
  • Experience in building new datasets, deriving insights from datasets, demonstrating proactive data-driven problem-solving skills.
  • Experience in contribution to high-impact open-source projects
  • Exceptional mathematical ability.
  • An advanced degree (e.g., M.S. or Ph.D.) in a relevant field with peer-reviewed publications in top machine learning conferences.

 

Successful candidates have the following traits:

  • Creative Problem Solver: Exceptional skills in analyzing intricate issues and formulating innovative AI technologies and methodologies.
  • Strategic Vision: A strategic outlook that ensures research activities are in alignment with overarching goals of the team and company, continuously pushing boundaries to address the most pressing challenges.
  • Purpose-Driven Research: Strong desire to engage in research that yields practical solutions and meaningful contributions to the company and the society at large.
  • Results-Oriented: Strong commitment to transforming research insights into impactful, actionable outcomes.



Recruiting Process

  • Application Review → Coding Test → Technical Interview (Online) → Culture Fit Interview

*  The process is subject to change, and we will contact you separately if you are selected to move forward with the recruiting process.