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Company Overview
This is a global technology, defense, and engineering group headquartered in Singapore. It’s a major player in various sectors, leveraging technology and innovation to solve real-world problems and contribute to a more secure and sustainable world.
Principal AI Engineer (Software), AI.DA STC
About the Role
A prominent technology company is seeking a Mid-to-Senior Software Engineer with extensive AI/ML experience to join their team. This role involves designing, building, and deploying a Computer Vision platform powered by AI agents. The successful candidate will be crucial in delivering scalable, production-grade systems that automate and accelerate ML workflows, encompassing model deployment, evaluation, and data pipelines. This is a hands-on position that combines software craftsmanship with AI expertise to advance automation in computer vision.
This is a 2-year contract position, based in Singapore, with the potential for conversion to a permanent role based on performance.
Key Responsibilities
Design and implement scalable agent-driven systems to automate Computer Vision MLOps workflows, including training, deployment, and evaluation.
Develop robust APIs and backend services to facilitate agent orchestration, memory management, and cross-component communication.
Integrate vector databases, data quality validation, and semantic search to enhance intelligent agent behavior.
Manage the entire software lifecycle, from development and testing to CI/CD automation and cloud deployment.
Ensure reliability and maintainability by incorporating logging, monitoring, and exception handling into design thinking.
Optimize performance and cost for storage and compute resources, particularly for vision-specific workloads.
Collaborate with researchers and domain experts to translate state-of-the-art concepts into functional code.
Must-Have Skills
Over 5 years of hands-on software engineering experience, with at least 2–3 years specifically building AI/ML systems.
Strong proficiency in Python development, including writing testable, production-grade code.
Proven experience with:
Designing and deploying CI/CD pipelines for ML systems.
Containerization and orchestration technologies such as Docker and Kubernetes.
Cloud infrastructure platforms like AWS, GCP, or Azure.
API development using frameworks such as FastAPI or Flask.
Database technologies, including SQL/NoSQL and vector databases (e.g., FAISS, Weaviate).
Familiarity with AI agent frameworks like LangChain, AutoGen, or CrewAI.
Solid understanding of Computer Vision workflows, including image classification, detection, and tracking.
Comfortable with software engineering best practices, including version control, code reviews, documentation, and modular design.
Nice-to-Have Skills
Demonstrated experience through personal projects, prototypes, or open-source contributions in AI, CV, or agents.
Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
Exposure to ML observability and performance monitoring tools (e.g., Grafana, Datadog, Prometheus).
Experience building simple user-facing interfaces for demos or internal tools (e.g., with Gradio or Streamlit).
Familiarity with unit testing frameworks (e.g., Pytest) and static analysis tools.
Prior experience in cross-functional collaboration, especially with researchers or product engineers.
Knowledge of LLM integration for autonomous agent systems.
Disclaimer
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