
AI Engineer -( IBM )TBD -788
eTeam APAC · HK
Weak hiring record · median 651 days open
All reasons
- Open 207 days
In its favour
- Still listed on the employer's own board
Also pls assign AI Engineer -( IBM )TBD -788
Job description -
- Develop and maintain AI application and ML models for tasks including natural language processing, computer vision ensuring high performance and scalability, with a strong focus on building and optimizing Retrieval-Augmented Generation (RAG) applications using Azure AI Search or related tools for efficient information retrieval and indexing.
- Research, design, and implement agentic AI workflows, enabling autonomous agents to handle complex, multi-step tasks through tool integration and decision-making logic.
- Explore and prototype latest AI and ML concepts, such as the Model Context Protocol (MCP), to enhance application interoperability and functionality.
- Conduct performance tuning, A/B testing, and monitoring of AI and ML systems in production environments, deploying solutions on OpenShift for containerized orchestration.
- Collaborate with software engineers to embed AI and ML capabilities into web /mobile applications, using Python for scripting, automation, and model development in prototype level
- Document technical designs, contribute to code reviews, and maintain best practices in AI and ML.
Requirements / Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, or a related field.
- 1+ years of professional experience in Data Science and Machine Learning or enterprise application development
- Experience in AI engineering or software development with AI components is advantage.
- Strong experience with cloud platforms (AWS, GCP, or Azure) for deploying AI and ML workloads, with specific hands-on knowledge of Azure AI Search and Copilot Studio for RAG and agentic implementations is a plus
- Excellent problem-solving skills and ability to work in agile environments.
- Strong communication skills, with the ability to explain complex AI and ML concepts to non-technical stakeholders.
- Experience with vector databases or knowledge graphs for RAG is a plus.
Skills
- Machine Learning
- Computer Vision
- Retrieval-Augmented Generation
- Azure AI Search
- Model Context Protocol
- OpenShift
- Python
- AWS
- GCP
- Azure
- Copilot Studio
- Vector Databases
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