Research Engineer, DMD/SVS (ARTC).

Agency for Science, Technology and Research (A*STAR); Singapore; On-site; USD 60,000 - 100,000; Full time

Job summary

An innovative public-private partnership is seeking a Senior Research Engineer to lead the development of scalable microservices for autonomous manufacturing applications. This dynamic role involves deploying machine learning models and implementing MLOps best practices, working closely with cross-functional teams to enhance system reliability and performance. Join a forward-thinking organization dedicated to advancing manufacturing solutions and upskilling the workforce. Ideal candidates will have a strong background in software development, AI/ML technologies, and a proactive attitude towards problem-solving.

Qualifications

• 5+ years of experience as a Software Developer/Engineer.
• Hands-on experience with Cloud Native Technologies and MLOps best practices.

Responsibilities

• Develop and maintain enterprise operations focusing on ML/AI systems.
• Implement MLOps best practices for model training and deployment.

Skills

C# .NET

Python

Angular

MLOps

AI/ML Technologies

Cloud Native Technologies

DevSecOps

Containerization

CI/CD Pipelines

Troubleshooting

Education

Bachelor's Degree in Computer Science/Engineering

Master's Degree in Computer Science/Engineering

Tools

Docker

Jenkins

Git

SonarQube

Artifactory

Job description

The Advanced Remanufacturing and Technology Centre (ARTC) is a public-private partnership consortium of more than 80 industry members. Our core mission is to develop and deploy advanced manufacturing solutions and upskill the workforce to drive local industry competitiveness. Smart Virtual Systems (SVS) Group is seeking a highly motivated Senior Research Engineer to implement highly available and scalable microservices-based applications and platforms for autonomous manufacturing applications. The candidate is expected to be independent and initiative-driven, demonstrating the capacity to discover innovative solutions to challenges.

We are looking for a talented and experienced Software Engineer with experience in MLOps/AI to join our dynamic team. In this role, you will play a key role in software development, focusing on deploying machine learning models and implementing MLOps best practices. You will work closely with our cross-functional research teams to streamline model deployment, and improve the scalability and reliability of systems.

The key roles and responsibilities include:

1. Develop, test, and maintain enterprise operations, with a focus on ML/AI systems.
2. Implement MLOps best practices to automate model training, deployment, and monitoring processes.
3. Optimize and implement machine learning algorithms and deep learning architectures.
4. Collaborate with data scientists and software engineers to integrate machine learning solutions into existing systems and deliver high-quality software products.
5. Optimize AI pipelines for scalability, reliability, and enhanced performance.
6. Conduct performance analysis and optimization to improve model efficiency and accuracy.
7. Stay updated on the latest advancements in software engineering, AI/ML technologies, and best practices.

Job Requirements

1. Bachelor's or Master's Degree in Computer Science/Engineering or relevant disciplines.
2. Minimum of 5 years of experience as a Software Developer/Engineer.
3. Hands-on experience with Cloud Native Technologies such as microservices, DevSecOps, and containerization.
4. Proficiency in designing and developing microservices and software systems using C# .NET, Python, and Angular.
5. Good understanding of CI/CD pipelines in distributed environments using Git, Artifactory, Jenkins, SonarQube, Docker registry, etc.
6. Experience deploying and managing microservices using container orchestration platforms (on-premises/public cloud).
7. Proactive attitude and ability to interface with multiple stakeholders.
8. Excellent troubleshooting, follow-through, and problem-solving skills, with attention to detail.
9. Excellent verbal and written communication skills.
10. Familiarity with deep learning architectures and natural language processing (NLP) techniques.