Job Description

What the role is:Opportunity We are seeking a talented AI Engineer to join our team at the Digital Hub Programme Centre. In this role, you will work on state-of-the-art AI Engineering initiatives, contributing to the design, development and deployment of AI systems at scale, while adhering to robust governance frameworks.What you will be working on:Key Responsibilities AI Engineering Roadmap Execution: Implement the AI Engineering roadmap through research, experimentation and hands-on development. MLOps & Tooling: Design, build and automate MLOps (CI/CD/CT/CM) pipelines and tools to streamline AI workflows (e.g. support seamless model deployment and lifecycle management). Implement domain-specific ML deployment, monitoring and retraining techniques for the AI community. Infrastructure: Develop and manage scalable infrastructure for AI development, deployment and monitoring. Governance & Compliance: Establish governance processes for AI systems, including release criteria, testing frameworks, retraining pipelines and continuous monitoring, to ensure compliance with safety and quality standards in AI systems.What we are looking for:Requirements Tertiary qualification in Computer Science, Information Systems, Computer Engineering or a related fields Minimum of 1 year of experience in MLOps preferred Strong programming skills with good grasp of software development best practices Strong desire to learn and grow within the AI engineering domain Team player with excellent communication skills Self-motivated and driven to deliver high-quality, reliable AI solutions Required skills Machine Learning Development: Experience with developing, deploying and scaling ML models (e.g. object detection) Software Engineering: Proficient in Python programming Proficient in Linux Operating Systems (E.g. Ubuntu, RHEL) Proficient in bash and yaml Proficient with version control (e.g. Git), Proficient with containerisation and orchestration (e.g. Docker/Podman, Kubernetes, OpenShift Container Platform) Previous experience would be advantageous MLOps Expertise: o Data and model versioning (E.g. DVC, clearml-datasets), model serving (e.g. vLLM, Triton Inference Server) and experiment orchestration (e.g. clearml) o Model testing (e.g. directional expectation and invariance testing, robustness testing such as adversarial AI, Brittleness and Explainability) o Model monitoring pipelines and retraining workflows (E.g. Drift Detection) Cloud Infrastructure: o Experience with hyperconverged infrastructure (HCI), storage (e.g. S3, NFS) and networking DevOps: o Familiarity with automation tools (e.g. Argo, Gitlab), monitoring dashboards (e.g. Prometheus/Grafana) and platforms (e.g. Kafka, Redis). o RESTful services (e.g. HTTPS, gRPC) Programming: o Rust, GoAbout Defence Science and Technology Agency:At DSTA, we are looking for Greater Minds who are passionate about developing advanced technological solutions to enhance Singapore's defence capabilities. You can look forward to a fulfilling career in an environment that promotes continuous learning and innovation. If you believe that you have the makings of a Greater Mind, begin your journey at DSTA to realise your full potential!

Defence Science and Technology Agency