ML Researcher (Computer Vision – Vision Language Model) at Boeing

Seoul, , South Korea -

Full Time

Start Date

Immediate

Expiry Date

20 Mar, 26

Salary

0.0

Posted On

20 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Computer Vision, Deep Learning, Neural Networks, Reinforcement Learning, Document AI, Optical Character Recognition, Vision-Language Models, Large-Language Models, Small-Language Models, Multimodal Techniques, Python, PyTorch, TensorFlow, Data Processing, Cloud Platforms

Industry

Aviation & Aerospace

Description

ML Researcher (Computer Vision – Vision Language Model) Company: Boeing Korea LLC About Us At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. Our Objectives Boeing Korea Engineering and Technology Center (BKETC) is seeking a highly skilled and motivated ML Researcher (Computer Vision – Vision Language Model) to join our cutting-edge research team. As an AI/ML Researcher, you will play a pivotal role in advancing the field of artificial intelligence and machine learning through innovative research, algorithm development, and the application of machine learning techniques focused on aircraft manufacturing, factory digitalization, etc. Your work will have a direct impact on developing state-of-the-art AI/ML models and systems that address real-world challenges and push the boundaries of intelligent systems. Job Responsibilities: Conduct groundbreaking research in the field of artificial intelligence and machine learning, focusing on techniques including but not limited to neural networks, deep learning, reinforcement learning, and other advanced models. Design, build and optimize document information extraction pipelines using multimodal techniques. Develop solutions based on Vision-Language Models(VLMs), including Large-Language Models(LLMs), Small-Language Models(SLMs) and emerging multimodal architecture. Integrate and fine-tune commercial or open source VLMs for tasks such as document layout analysis, key value extraction, classification, summarization and semantic parsing. Collaboration with MLOps engineers to deploy scalable, production-ready inference services and APIs. Stay current with the latest advancements in AI and machine learning, specifically OCR(Optical Character Recognition), VLMs, LLMs/SLMs and document AI research. Collaborate with cross-functional teams to define research objectives, scope, and methodologies, and contribute to project planning and execution. Basic Qualifications (Required Skills/Experience): Master’s degree with at least three years of work experience or Ph.D. degree in Engineering, Computer Science, Mathematics, or Statistics. Extensive experience in designing and implementing AI/ML models using machine learning techniques, including neural networks and deep learning architectures. Practical experiences utilizing and/or fine-tuning LLMs and SLMs for multimodal reasoning and extraction tasks. Hands-on experience with OCR and document AI, including traditional approaches Proficiency in programming languages such as Python, and experience with machine learning libraries (PyTorch, TensorFlow, etc.). In-depth knowledge of computer vision and AI/ML fundamentals, including but not limited to supervised and unsupervised learning, reinforcement learning, and model evaluation techniques. Strong analytical and problem-solving skills, with the ability to formulate research questions, design experiments, and interpret results. Experience with large-scale data processing, distributed computing, and cloud platforms is a plus. Excellent communication skills, both written and verbal, with the ability to explain complex technical concepts to both technical and non-technical audiences. Proficient in English to effectively collaborate with an international team. Preferred Qualifications (Desired Skills/Experience): Ph.D. degree with at least two years of work experience in Engineering, Computer Science, Math, or Statistics The ideal candidate is a self-starter and someone who works well within a team Good to have at least an intermediate level of knowledge in server engineering, including resource management on multi-GPUs across multiple servers. Good to have at least an intermediate level of knowledge in relevant industries, such as aviation, manufacturing or commercial operations. Nice to have field experience in developing and executing projects using machine learning techniques to optimize processes, reduce downtime, and improve quality. Nice to have winning experience in machine learning or data science competition challenges. Nice to have publication records in top-tier machine learning or artificial intelligence conferences. Applicable and appropriate educational/certification credentials from an accredited institution and/or equivalent experience is required. Language Requirements: Not Applicable Education: Bachelor's Degree or Equivalent Relocation: Relocation assistance is not a negotiable benefit for this position. Security Clearance: This position does not require a Security Clearance. Visa Sponsorship: Employer will not sponsor applicants for employment visa status. Contingent Upon Award Program This position is not contingent upon program award Shift: Not a Shift Worker (Korea, Republic of) You can do work that enables all of humanity to take flight. Our teammates in more than 65 countries grow their careers across commercial airplanes, space, defense, sustainability and other areas. Here, you can contribute to what matters most in your career, in your community and around the world. Find answers to questions about applying, interviews, benefits, and more on FAQ page Boeing is committed to providing reasonable accommodations/adjustments to applicants with disabilities. Visit our accommodations page for more info.

Responsibilities

Conduct groundbreaking research in artificial intelligence and machine learning, focusing on advanced models and techniques. Develop solutions based on Vision-Language Models and collaborate with cross-functional teams to define research objectives and methodologies.