Deskripsi Pekerjaan
The Agency for Science, Technology and Research (A*STAR) is Singapore's lead public sector agency dedicated to fostering scientific discovery and technological innovation. Our Artificial Intelligence for Drug Discovery (AIDD) team is at the vanguard of integrating cutting-edge artificial intelligence with biomedical science to accelerate the discovery and development of novel life-saving therapies.
We are seeking an exceptionally talented and driven Scientific Platform Engineer to join our dynamic, world-class team in Singapore. In this pivotal role, you will architect, build, and maintain the core platform infrastructure that empowers our scientists and machine learning engineers to perform groundbreaking research at an unprecedented scale. You will be the bridge between software engineering, MLOps, and computational biology, ensuring that our cutting-edge AI models are deployed reliably, efficiently, and scalably.
Your work will have a direct impact on the development of novel algorithms for molecular generation, protein structure prediction, and biological property analysis. You will manage petabyte-scale computational workloads, optimize complex model inference pipelines, and ensure the highest standards of security and reliability for our scientific computing environment. If you are passionate about leveraging technology to solve the most challenging problems in biomedical science, this is the perfect opportunity to make a real difference.
Why Join A*STAR?
- Impact: See your engineering contributions translate directly into real-world scientific breakthroughs.
- Innovation: Work at the intersection of AI and drug discovery, tackling unique challenges.
- Environment: Collaborate with world-leading researchers with access to unparalleled resources.
- Growth: We invest heavily in our people, offering top-tier benefits and career development.
Tanggung Jawab
- Architect, build, and maintain scalable, high-performance computing platforms on cloud infrastructure (AWS/GCP) to support AI-driven drug discovery workflows.
- Develop and optimize CI/CD pipelines for continuous integration and deployment of machine learning models and scientific software.
- Design and implement robust data pipelines for processing and managing large-scale chemical and biological datasets (genomics, proteomics, microscopy).
- Collaborate closely with computational chemists and biologists to translate scientific requirements into technical solutions.
- Implement monitoring, logging, and alerting systems to ensure platform reliability and model performance in production.
- Evaluate and integrate new technologies and frameworks to improve platform efficiency and capability.
- Mentor junior engineers and contribute to best practices in software development and MLOps within the team.
Kualifikasi
- Bachelor's, Master's, or PhD in Computer Science, Engineering, Computational Biology, or a related quantitative discipline.
- 5+ years of professional experience in software engineering, platform engineering, or MLOps.
- Deep expertise in Python, along with proficiency in a systems language (Go, Rust, Java, or C++) is a plus.
- Strong experience with containerization (Docker) and orchestration (Kubernetes) in a production environment.
- Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
- Experience with workflow orchestration tools (e.g., Airflow, Nextflow, Prefect).
- Familiarity with machine learning frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow, Kubeflow).
- Knowledge of drug discovery, cheminformatics (RDKit, OpenEye), or bioinformatics is a significant plus.
- Excellent communication skills and the ability to work effectively in an interdisciplinary team.