Principal Computer Vision Engineer

About the Role

RGE Digital is seeking a Principal Computer Vision Engineer to lead the advancement of AI-driven automation in agriculture and industrial sectors. This strategic position focuses on developing cutting-edge computer vision solutions harnessing drone and satellite imagery to enhance operational efficiency across diverse segments such as forestry, manufacturing, and renewable energy worldwide.

Company Overview

RGE Digital spearheads the digital transformation of RGE’s extensive business operations through innovative use of sensors, analytics, cloud technology, and AI. With a presence across four continents, managing approximately $40 billion in assets and employing roughly 80,000 staff, RGE adopts a product-centric approach emphasizing prototyping, piloting, and scaling advanced analytics to tackle major industry challenges.

Key Responsibilities

• Lead the architectural design and strategic development of dependable, scalable, and precise AI-based computer vision models.
• Develop comprehensive pipelines encompassing data acquisition, annotation, and machine learning operations for deployment at edge and cloud scales.
• Convert intricate business needs into clear technical specifications and phased development plans.
• Provide mentorship to data scientists and engineering teams, promoting high technical standards and innovation.
• Stay abreast of emerging AI and data science trends to incorporate relevant innovations into RGE’s technology stack.

Required Qualifications

• Minimum seven years of experience designing and deploying deep learning and computer vision solutions in live production environments.
• Advanced academic credentials preferred, such as a Master’s or PhD in Computer Vision, Machine Learning, or Computer Science.
• Expert-level programming skills in Python along with proficiency in frameworks like PyTorch, TensorFlow, and OpenCV.
• Robust understanding of machine learning operations (MLOps) and data engineering methodologies.
• Proven record of employing analytical skills to resolve complex business challenges.

Preferred Technical Expertise

• Proficiency in working with Foundation Models and Vision-Language Models.
• Knowledge of current state-of-the-art architectures including DINOv3, SAM 3 (Segment Anything Model), DETR, and YOLO.
• Experience in Self-Supervised Learning techniques and handling datasets that are sparse or lack labels.
• Skill in processing multi-spectral satellite images and geospatial datasets.