Job Summary

About the Role

We are seeking highly experienced Senior AI Engineers to lead the design, implementation, and scaling of  AI infrastructure. In this role, you will bridge the gap between data science and software engineering by building robust, automated pipelines and establishing best practices for model development, deployment and lifecycle management.

We are looking for someone who is passionate about building highly efficient, reusable, and developer-friendly AI systems.

Why Join Us

At the Agency for Science, Technology and Research (A*STAR), Singapore’s leading public sector R&D agency, you will work at the vibrant intersection of frontier scientific research and real-world industrial translation. Engineers at A*STAR have the unique opportunity to design and build AI infrastructure that scales across incredibly diverse, multi-disciplinary domains—from advanced manufacturing and digital healthcare to sustainability and transportation.

A*STAR heavily invests in its engineers’ growth, offering a highly collaborative research culture, competitive benefits, robust pathways for continuous learning, and the unique chance to work on nationally-significant Smart Nation initiatives that impact lives globally.

What You Will Do

• Pioneer Multimodal AI: Design and develop advanced deep learning models capable of understanding, aligning and reasoning over complex audio and multimodal inputs.
• Bridge Research & Reality: Translate state-of-the-art AI research into practical, real-world systems using strong system-level thinking and engineering rigor.
• Deploy at Scale: Architect and build scalable, low-latency deployment systems that ensure robustness, high efficiency, and absolute production readiness.
• Accelerate with GenAI: Apply cutting-edge Generative AI techniques, leveraging AI-assisted development tools to supercharge your data engineering, model training, and prototyping.
• Own the End-to-End Pipeline: Build comprehensive, seamless pipelines—from raw data processing and training frameworks to evaluation suites and deployment workflows.
• Rapid Prototype & Iterate: Foster an agile environment where you can rapidly prototype new ideas and successfully transfer cutting-edge technology into operational environments.
• Collaborate to Integrate: Work closely with multidisciplinary teams to seamlessly weave audio intelligence into broader, complex enterprise AI systems.

Requirements

• Proven Scale: 6+ years of experience in Software Engineering, Platform Engineering, or DevOps, with at least 3+ years strictly dedicated to MLOps, AI Infrastructure, or ML Engineering in a high-traffic, production environment. Fresh graduates with great interest in mastering advanced AI capabilities are welcome to apply
• Architectural Vision: Demonstrated experience designing, building, and maintaining end-to-end ML platforms from the ground up, moving beyond single-model deployments to centralized organizational infrastructure.
• Engineering Rigor: Deep proficiency in Python and strong knowledge of at least one high-performance backend language (e.g., Go, C++, Rust, or Java). You write clean, testable, and production-grade code.
• Cloud & Container Mastery: Experience with cloud-native architectures (AWS, GCP, or Azure) and deep fluency in containerization and orchestration (Docker, Kubernetes, Helm).