Junior AI Engineer

Play a key role in automating, monitoring, and continually improving our ML/AI driven operations. The ideal candidate should have a strong passion for bridging machine learning, DevOps, and data science, coupled with the ability to architect and deploy scalable ML solutions that enhance operational efficiency, drive business transformation, and foster ML innovation.

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Job Description:

Service Deployment and Ongoing Support:

Coordinate release pipelines for MLAI services, manage container/orchestration systems, ensure version control, and monitor performance metrics for continuous improvement.
Production-ready AI services with stable runtime environments, documented deployment processes, and optimized performance tracking.

Integrated Model Lifecycle and CI/CD:

Automate model building, testing, and validation pipelines. Integrate version control and environment management; and enable continuous monitoring for feedback-driven improvements
Seamless end-to-end ML workflows, faster iteration from development to production, and robust model performance at scale

Continuous Monitoring and Observability:

Configure AI driven alerts, integrate with monitoring systems, and maintain real-time dashboards
Early anomaly detection, centralized observability, and reduced time to detect and respond.

Incident Response and Troubleshooting:

Correlate AI insights across data sources, coordinate response teams, and document lessons to enhance models.
Swift root-cause identification, comprehensive RCA documentation, and continuous process improvements.

Policy and Risk Oversight:

Establish AI approval workflows, maintain audits for data/model changes, and align operations with regulations.
Transparent, compliant AI processes, defined risk assessments, and robust governance structures.

Job Requirements:

Open for Malaysian citizen ONLY
Minimum at Bachelor’s in Computer Science, Artificial Intelligence, Data Science, or a related field.
Minimum 1+ experience related
Strong Python programming foundation with a focus on clean, efficient code.
Eagerness to explore and implement ML, deep learning, and GenAI models.
Experience in deep learning libraries (e.g., TensorFlow, PyTorch, Transformers, Keras)
Experience in NLP and vision tasks
Experience in Version control using Git
Experience in RESTful API integration
Familiarity with model lifecycle from training to deployment

MUST:

NPL: 1 year
Deep Learning: 1 year
AI: 1 year
CI/CD: 1 year

Good to have:

Exposure to GenAI tools and frameworks (e.g., OpenAI, Hugging Face Transformers, LangChain, RAG).
Understanding of learning paradigms: supervised, unsupervised, reinforcement learning.
Familiarity with containerization tools (Docker, Podman) and cloud environments.
Experience with MLOps tools or platforms (e.g., Dataiku, MLflow, FastAPI).
Basic knowledge of UI/UX or front-end integration for AI tools.

Send your resume to: ttmy@tg-hr.com