Experienced AI/MLOps Engineer Hot

Job Description

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.

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 AI/MLOps Engineer to join our cutting-edge research team. As an AI/MLOps Engineer, you will play a pivotal role in advancing the field of artificial intelligence and machine learning through innovative research, algorithm development , and the deployment and maintenance 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:

• Develop, deploy, and maintain ML pipelines, architectures, algorithms, and models
• Build software verification systems that comply with aviation safety requirements
• Work effectively within an international team using English communication

Basic Qualifications (Required Skills/Experience):

• Bachelor’s degree with 5 years’ related work experience or Master degree with 3 years’ related work experience or PhD in Engineering, Computer Science, or Mathematics
• In-depth knowledge of machine learning, data science and engineering
• Proficiency in multiple programming languages (e.g., Python, JavaScript, TypeScript, Golang)
• In-depth knowledge of Front-end framework (e.g., React, NextJS)
• In-depth knowledge of Back-end framework (e.g., FastAPI)
• In-depth knowledge of model deployment on infrastructure-agnostic environment (e.g., Kubernetes, Docker)
• In-depth experience with Cloud platform and service (e.g., AWS, Azure, GCP)
• In-depth experience with CI/CD tools (e.g., GitLab CI, Argo CD, Jenkins) and monitoring tools (e.g., Grafana, Prometheus)
• In-depth ML Model development (e.g., PyTorch, TensorFlow) and deployment experiences (e.g., ONNX)
• Effective verbal and written English communication skill

Preferred Qualifications (Desired Skills/Experience):

• Master’s, Ph.D., or equivalent in Engineering, Computer Science, or Mathematics
• In-depth experience with machine learning frameworks (e.g., TensorFlow, Keras, PyTorch)
• In-depth knowledge of system frameworks (e.g., Kubeflow, MLflow)
• Participation in software competitions and well-organized public code repositories are a plus

Job Responsibilities:

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Applications for this position will be accepted until Aug. 11, 2025

Relocation

Relocation assistance is not a negotiable benefit for this position.

Visa Sponsorship

Employer will not sponsor applicants for employment visa status.

Shift

Not a Shift Worker (Korea, Republic of)

Equal Opportunity Employer:

We are an equal opportunity employer. We do not accept unlawful discrimination in our recruitment or employment practices on any grounds including but not limited to; race, color, ethnicity, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military and veteran status, or other characteristics covered by applicable law.

We have teams in more than 65 countries, and each person plays a role in helping us become one of the world’s most innovative, diverse and inclusive companies. We are proud members of the Valuable 500 and welcome applications from candidates with disabilities. Applicants are encouraged to share with our recruitment team any accommodations required during the recruitment process. Accommodations may include but are not limited to: conducting interviews in accessible locations that accommodate mobility needs, encouraging candidates to bring and use any existing assistive technology such as screen readers and offering flexible interview formats such as virtual or phone interviews.