Editorial summary

The company is seeking a permanent AI Engineer to lead the architecture, development, and deployment of machine learning solutions for geospatial applications. The role involves designing scalable AI systems, collaborating with software engineers to integrate AI components, and ensuring system reliability through best practices in MLOps. Candidates should have strong technical expertise in machine learning and system integration. The position offers a salary of 7,000.

This summary is AI-generated and may contain inaccuracies. Please refer to the full job description below.

Job description

[This job id 29244 first appeared in Job-Q.com on 02 Sep 2026]

Responsibilities

●     Provide technical leadership in the architecture, development, and deployment of production-grade machine learning solutions forgeospatial applications.

●     Architect scalable machine learning systems and partner with software engineers to integrate AI components into end-to-end platforms.

●     Own model performance and system reliability by driving best practices in MLOps, deployment, monitoring, and continuous improvement.

●     Work closely with product, business development, and sales teams to translate business objectives into well-defined technical requirements and delivery plans.

●     Mentor engineers and guide technical decisions, while providing technical support for pre- and post-sales activities as required.

Requirements

●     Background in Computer Science, Electrical Engineering, or a related discipline.

●     At least 5 years of relevant experience delivering production machine learning solutions.

●     Strong foundation in machine learning and deep learning, including model development, evaluation, and optimization.

●     Proficient in Python, with hands-on experience in common ML frameworks (e.g., PyTorch, scikit-learn) and computer vision libraries (e.g., OpenCV).

●     Experience deploying and operating ML services, including API development (e.g., Flask/FastAPI/Node.js) and containerisation(e.g., Docker).

●     Experience with large language models, retrieval-augmented generation, retrieval optimization, and graph databases is an advantage.

●     Self-motivated and proactive, with strong ownership, stakeholder management, and the ability to mentor and work effectively across teams.

Work Location: Central/North

(EA Reg No: 20C0312)

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