Senior Scientist (DMD Division/CPPS Group), SIMTech

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

A*STAR Research Entities in Singapore is seeking a Machine Learning Scientist to lead R&D applying AI/ML to manufacturing challenges, including process monitoring, quality improvement, and reconfigurable systems.

You will develop and deploy ML pipelines with MLOps, work with time series data for predictive modeling, and collaborate across disciplines, using Docker to ensure scalable, reproducible workflows. Proficiency with PyTorch/TensorFlow and cloud familiarity is a plus.

Qualifications

• PhD in Computer Science, Engineering, or related ML field required.
• Experience deploying ML in production environments.
• Proficient with time series analysis for monitoring quality.
• Familiar with Docker and MLOps best practices.
• Knowledge of advanced ML techniques like few-shot and continual learning.

Responsibilities

• Lead ML R&D for smart manufacturing projects.
• Develop and deploy ML pipelines with MLOps.
• Work with time series data for predictive modeling.
• Apply advanced ML methods: few-shot, transfer, continual learning.
• Collaborate in a multidisciplinary team.
• Ensure scalable and reproducible ML workflows using Docker.

Skills

Machine learning

Time series analysis

Python

Collaboration

Education

PhD in CS/Engineering

Tools

Docker

MLOps

PyTorch

TensorFlow

Job description

Role Summary

We seek a Machine Learning Scientist to lead and support R&D in applying AI/ML to manufacturing challenges, particularly in process monitoring, quality improvement, and reconfigurable systems.

Key Responsibilities

• Conduct research on ML/AI applications in smart manufacturing.
• Develop & deploy ML pipelines with MLOps practices.
• Work with time series data for predictive modeling.
• Apply advanced ML methods: few-shot, transfer, continual learning.
• Collaborate in a multidisciplinary team.
• Ensure scalable and reproducible ML workflows using Docker.

Requirements

• PhD in Computer Science, Engineering, or related field (focus on ML/AI).
• Proven experience with ML in production environments.
• Proficient in time series analysis & quality monitoring systems.
• Familiar with Docker and MLOps best practices.
• Knowledge of advanced ML techniques (few-shot, continual learning, etc.).

Preferred Skills

• Knowledge of predictive shopfloor analytics, especially predictive maintenance management and predictive quality management
• Background in smart/digital manufacturing.
• Familiarity with Industry 5.0 and reconfigurable systems.
• Strong Python skills; experience with ML frameworks (PyTorch/TensorFlow).
• Exposure to cloud platforms (AWS, GCP, Azure).