Senior Research Scientist (DMD/CPPS), SIMTech

A*STAR - Agency for Science, Technology and Research; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

A*STAR - Agency for Science, Technology and Research seeks a Machine Learning Scientist to drive cutting-edge R&D applying AI/ML to advanced manufacturing challenges. You will develop ML solutions for process monitoring, quality improvements, and reconfigurable systems to accelerate digital transformation in industry.

The role emphasizes research and production ML practices, strong Python skills, and experience with Docker and cloud platforms (AWS/GCP/Azure).

Qualifications

• 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.).

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.

Skills

ML in production

Time series analysis

Python programming

MLOps

Collaborative work

Education

PhD in CS/Engineering or related

Tools

Docker

PyTorch

TensorFlow

AWS

GCP

Azure

Job description

Role Summary

We are seeking a Machine Learning Scientist to drive and support cutting-edge R&D initiatives that apply Artificial Intelligence (AI) and Machine Learning (ML) to advanced manufacturing challenges. The role focuses on developing innovative solutions for process monitoring, quality enhancement, and reconfigurable manufacturing systems to accelerate digital transformation in industry.

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).