Ai Software Engineer

1 day ago

Singapore HIVERLAB PTE. LTD. Full time

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.

**Key Responsibilities**
- 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.
- 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.

**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.

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