[T02] AI Engineer
Summary
Lead the architecture and deployment of production-grade ML solutions for geospatial applications, focusing on Python-based model development, API services, and MLOps practices.
Key Responsibilities
- Lead the architecture, development, and deployment of production-grade ML solutions for geospatial applications.
- Design scalable ML systems and integrate AI components into end-to-end platforms with software engineering teams.
- Drive MLOps best practices, including deployment, monitoring, model performance, reliability, and continuous improvement.
- Translate business objectives into technical requirements and delivery plans in collaboration with product, sales, and business development teams.
- Mentor engineers, guide technical decisions, and support pre- and post-sales activities.
Requirements
- Degree in Computer Science, Electrical Engineering, or a related discipline.
- 5+ years of experience delivering production ML solutions.
- Strong knowledge of machine learning/deep learning, including model development, evaluation, and optimisation.
- Proficient in Python with hands-on experience in PyTorch, scikit-learn, OpenCV, or similar frameworks.
- Experience deploying ML services, developing APIs (Flask/FastAPI/Node.js), and using Docker.
- Experience with LLMs, RAG, retrieval optimisation, and graph databases is an advantage.
- Strong ownership, communication, stakeholder management, problem-solving, and mentoring skills.
(EA Reg No: 20C0312)
Please email a copy of your detailed resume to qianyu@talentsis.com.sg for immediate processing.
Only shortlisted candidates will be notified.