AI/ML Ops Engineer
On-siteSeoul, Seoul, South Korea
Seoul, Seoul, South KoreaOn-siteFull TimeSenior LevelBachelors DegreeEnterprise
Full TimeSenior LevelBachelors DegreeEnterprise
Job Summary
Develop, deploy, and maintain ML pipelines, architectures, algorithms, and models while building software verification systems that comply with aviation safety requirements. Work effectively within an international team using English communication to advance artificial intelligence and machine learning through innovative research and algorithm development focused on aircraft manufacturing and factory digitalization. This role contributes to developing state-of-the-art AI/ML models that address real-world challenges and push the boundaries of intelligent systems at Boeing Korea's BKETC research team.
Required Qualifications
- Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement
- In-depth knowledge of machine learning, data science and engineering
- Proficiency in multiple programming languages (e.g., Python, JavaScript, TypeScript, Golang)
- Effective verbal and written English communication skill
- Location: This position is expected to be 100% onsite
- The selected candidate will be required to work onsite at BKETC Office and the listed location site
- Travel: Some travel may be required, up to 10% of the time
- This requisition is for a locally hired position
- 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
- Shift: Not a Shift Worker (Korea, Republic of)
Desired Qualifications
- 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 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)
- In-depth knowledge of system frameworks (e.g., Kubeflow, MLflow)
- Participation in software competitions and well-organized public code repositories are a plus
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