Machine Learning Engineer – Computer Vision

Xantory is seeking a Machine Learning Engineer – Computer Vision to build the capability for their vertical-farming control platform. This role is based in Dubai and involves hands-on, production-focused work with regular on-site farm tasks. Join us to develop cutting-edge AI for smart factory solutions.

As the first machine-learning engineer, you will be responsible for developing computer vision models to analyze plant growth, detect issues, and optimize farming processes. Success will be measured by the reliable performance of these models in production environments.

We are looking for a proactive individual to own the end-to-end development of our computer vision capabilities, from data collection and model training to deployment and integration with our existing platform. Apply now to shape the future of indoor farming technology!

Company Overview

Xantory is a Dubai-based company specializing in industrial automation and smart factory solutions. We design and deliver container-based Indoor Farming Systems (IFC), customized production lines, and integrated smart manufacturing solutions for clients in the region and internationally. Our vertical-farming control platform manages climate, light, irrigation, and dosing, and we are now expanding its capabilities with advanced machine learning and computer vision.

Quick Details

• Salary Range: Not Specified
• Job Type: Full-time
• Qualifications: bachelors-degree
• Experience: 4 Year+

Key Responsibilities

• Specify and implement imaging setups for racks and trays, including camera selection, placement, and lighting.
• Build and manage labelled image datasets from our own crops, starting with on-site data collection.
• Train and deploy models for plant detection, growth-stage recognition, canopy coverage, stress/disease indication, and harvest readiness.
• Choose appropriate computer vision approaches (classification, detection, segmentation, anomaly detection) and validate them rigorously.
• Deploy inference at the edge and on the site server, optimizing for accuracy, latency, and hardware constraints.
• Combine vision data with sensor and yield data to analyze growing recipes and explain outcomes.
• Integrate models as services within the existing platform, ensuring version control, performance monitoring, and retraining.

Requirements

• 4 years of hands-on computer vision experience with PyTorch or TensorFlow, including a successfully deployed vision system.
• Experience building image datasets from scratch, including quality control and handling small/shifting datasets.
• Practical experience with cameras and video pipelines, including exposure, color under artificial light, and calibration.
• Familiarity with edge inference (ONNX, TensorRT, NVIDIA Jetson, Raspberry Pi) is advantageous.
• Solid Python and ML fundamentals, including leakage-safe validation.
• Comfortable in a production engineering environment (Git, code review, tests, containers).
• Clear written and spoken English communication skills.

Benefits

• Opportunity to be the first machine-learning engineer and build a critical capability from the ground up.
• Work on cutting-edge AI technology in the rapidly growing vertical farming and smart factory sector.
• Hands-on experience with data collection, model training, and edge deployment.
• Contribute to a production-focused role with direct impact on real crops and operational decisions.
• Collaborate with a dynamic team in a Dubai-based innovative company.