Founded in 2014 with HQ in Singapore, Hiverlab provides unique Spatial Intelligence products and solutions to help organizations intelligently organize / present information and automate processes, making emerging tech accessible and secure for a transparent and sustainable world.
We strive to democratise the interoperability of emerging technologies such as XR, IoTs, Cloud Computing, 5G, Data Analytics, AI / Machine Learning, Robotics & Automation, etc., all of which collectively enabling Spatial Digital Twins and Spatial Computing.
To date, we serve hundreds of enterprise customers in 20+ countries, from a few sectors such as logistics, manufacturing, built environment, medical health, smart city and critical infrastructure, etc. We also constantly collaborate with the public sector and academia - for example, we have been a sponsor to NUS STePS since 2017.
For more information, please visit: https://www.hiverlab.com .

REQUIRED / PREFERRED QUALIFICATIONS & SKILLS

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (e.g., Mathematics, Physics) with strong programming skills.
• Proficiency in backend technologies such as FastAPI, Flask, or Node.js.
• Familiarity with AI/ML tools and frameworks such as PyTorch, Hugging Face, or LangChain.
• Strong understanding of software architecture, design patterns, and databases (SQL/NoSQL).
• Hands-on experience deploying ML models in production using tools such as Docker, Kubernetes, and REST APIs.
• Familiarity with cloud platforms, with a preference for Azure, followed by AWS.
• Self-motivated, proactive, restorative, and a strong team player with a high sense of responsibility and attention to detail.
• Strong communication skills and strategic thinking abilities. Eagerness to learn new knowledge.

• Design, develop, and deploy full-stack applications that integrate AI/ML models.
• Collaborate with other teams (e.g. Business Development, 3D Engineering, etc.) to productionize and monitor AI/ML models.
• Build scalable backend APIs and services to support AI features.
• Implement data pipelines, ETL processes, and model inference infrastructure.
• Deploy, monitor, and maintain infrastructure and application resources across cloud, on-premise, or hybrid environments, with automation wherever possible.
• Ensure code quality through testing, documentation, and adherence to best practices. Write clean, optimized, and well-documented code with a focus on performance, reliability, scalability, and reusability across multiple projects.
• Participate in architecture design, code reviews, and project planning.
• Mentor interns and support their technical growth.