AI Training Environment Developer (FAIT)

YASH Technologies

Python Programming – for AI / ML model development and data processing.

Real-Time Task Scheduling & Monitoring – for AGV job assignment and fleet coordination.

Work Order (WO) Optimization – for intelligent routing and task prioritization.

Predictive Maintenance Modeling – using historical data and sensor logs.

Issue Tracking Algorithms – for anomaly detection and resolution.

Log Analysis & Feature Extraction – for training models and system diagnostics.

TensorFlow / PyTorch – for deep learning applications.

Scikit-learn / XGBoost – for classical ML approaches.

Time Series Forecasting – for maintenance and usage prediction.

Data Pipeline Tools (e.g., Airflow, Kafka) – for scalable data ingestion and processing.

Experience with AGV or MES systems – for domain-specific insights.

Key Responsibilities

• Design and develop a global AI Training environment that dynamically allocates compute and GPU resources based on model training requirements.
• Integrate the training environment with the existing Factory MLOps platform for model tracking, cataloging, and deployment using tools such as MLFlow and KServe.
• Develop a common UI portal for Data Scientists and Communities of Practitioners (CoP) to access the environment, and provide APIs for integration with other factory systems.

Seniority level

Associate

Employment type

Contract

Job function

Information Technology

Industries

Information Services and Manufacturing

Location

Penang, Malaysia

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