友邦科技
AI Engineer-GIO
Skills
7 months ago
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Important information
Contract type:
Permanent
Location:
Chengdu, Sichuan, China
Work mode:
Onsite
Published on:
7 August 2026
What they need
该职位来源于猎聘 Position Objective: The AI Engineer is responsible for designing, implementing, and maintaining robust MLOps pipelines to enable scalable, secure, and reliable deployment of machine learning models in production. The role bridges data science and engineering, ensuring seamless integration of AI solutions into enterprise systems and driving operational excellence in AI initiatives.
Roles and Responsibilities
Design and implement MLOPS, i.e. set of tools and operating models used to deploy & maintain & monitor AI/ML models in production reliably and efficiently (15%)
Support AI/ML solutions go-live integration (15%)
Act as a bridge between data scientists and IT & data engineers & data architects, especially during development & production architecture design & set-up (15%)
Design & build the technical architecture to deploy & maintain AI/ML in production (15%)
Refactor AI/ML model training / testing code into CI-CD pipelines (15%)
Test and optimize machine learning models and algorithms before they go in production (15%)
Assist in monitoring and retraining models (10%)
'Performs other responsibilities and duties periodically assigned by supervisor in order to meet operational and/or other requirements
Minimum Job Requirements Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field
8+ years of experience in MLOps, software engineering, or machine learning
Strong proficiency in Python and ML frameworks (PyTorch)
Experience with containerization and orchestration tools (Docker, Kubernetes)
Familiar with Dockers, Kubernetes, API Design, MCP
Familiar with main agentic framework
Familiarity with cloud platforms (Azure preferred)
Knowledge of CI/CD, model monitoring, and ethical AI frameworks
Strong communication skills in English, both spoken and written
Relevant certifications (e.g., Azure ML, AWS ML, Kubernetes) are a plus
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