Engineer/ Senior Engineer/ Principal Engineer (AI Engineering), Digital Hub
Job no: 2002968
Work type: Permanent
Location: DSTA Singapore
The Defence Science and Technology Agency (DSTA) brings you to the forefront of cybersecurity, digital transformation and engineering. From working on software development and systems integration to unmanned technologies and artificial intelligence, you can have an impact on Singapore’s defence.
Achieve your fullest potential with opportunities to build your technical expertise and hone your competencies in diverse domains. You can also expect an immersive learning experience, where you will work with bright minds and collaborate with global industry experts.
DSTA is recognised as one of the top 10 employers in the Engineering & IT sector, where our engineers and IT professionals work alongside procurement specialists to deliver state-of-the-art capabilities for Singapore’s peace and security.
Internship opportunities and a meaningful career await you.
Learn more about DSTA at https://www.dsta.gov.sg. You may also email us at email@example.com if you have any enquiries pertaining to careers.
We are looking for an individual to join us in our Digital Hub Programme Centre where you will participate in AI Engineering initiatives. The role will require you to execute the AI Engineering roadmap through research, experimentation and implementation of
- MLOps (CI/CD/CT) pipelines and tools
- Supporting infrastructure for AI development and deployment, and
- Governing processes and release criteria
Some examples of your work could include,
- Design and build pipelining tools and processes to automate the MLOps process
- Research, design and build ML-specific testing and remediation techniques (E.g. Unit tests, Robustness tests) for the AI community
- Research, design, develop and optimize domain specific ML deployment, monitoring and retraining techniques for the AI community
- Tertiary qualification in Computer Science, Information Systems, Computer Engineering, or related fields
- 1 year of experience in MLOps domain/ area preferred.
- Excited to gain knowledge in a new domain
- Team player with good communication skills
- Passionate and self-motivated
- Required skills
- ML development
- Basic ML tasks (E.g. Object Detection as a ML CV task).
- Modular coding for Machine Learning (Pipelines)
- Data preprocessing and ML model training using any ML frameworks
- Software Engineering and Infrastructure.
- Programming: Python
- Scripting: Bash
- Linux Operating Systems (E.g. Debian, RHEL)
- Version control (E.g. git)
- Containerization and Container Orchestration (E.g. Docker, Kubernetes.)
- Preferred skills (Previous experience would be advantageous)
- Data Versioning
- Experiment Orchestration (E.g. MLOps E2E Tools)
- Model Versioning
- Model Serving (E.g. Inference engines)
- Unit Testing (E.g. Directional Expectation Tests, Invariance Testing)
- Robustness Testing (E.g. Adversarial AI, Brittleness, Explainability)
- Model/Data Monitoring pipelines
- Model retraining pipelines
- Labeling (E.g. multi-type labelling tools)
- Cloud Infrastructure
- Hyperconverged Infrastructure (HCI)
- Storage (E.g. S3)
- Automation (E.g. Jenkins)
- Monitoring dashboards (E.g. Prometheus/Grafana.)
- Messaging (E.g. Kafka.)
- RESTful web services (E.g. https, gRPC)
Advertised: Singapore Standard Time
Applications close: Singapore Standard Time
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