Senior Machine Learning Engineer - Computer Vision

About the role

The ASUS Robotics & AI Center is looking for a Senior Machine Learning Engineer to join its global R&D team. The role leads the design and delivery of advanced computer vision and perception systems for next-generation autonomous platforms, and suits a seasoned, self-directed engineer who can drive technical decisions, mentor others and work in a collaborative, multidisciplinary team.

Key responsibilities

• Lead the design and development of machine learning systems for computer vision and perception tasks.
• Optimize models for real-time performance on embedded and edge computing platforms.
• Build and maintain robust perception pipelines integrating data from cameras and other sensors.
• Evaluate and implement state-of-the-art deep learning techniques in object detection and visual tracking.
• Drive technical decisions and guide architecture, tooling and best practices across the team.
• Design and run experiments, including simulation and real-world field testing, to validate model performance.
• Maintain and improve datasets, pipelines and tools for efficient model training and deployment.
• Work with robotics, systems and software engineers to deliver production-ready solutions.

Required profile

• Bachelor's degree or higher in computer science, electrical engineering, robotics or a related field.
• 8+ years of experience developing and deploying machine learning models for computer vision or perception applications.
• Strong problem-solving skills and the ability to lead technical work in a fast-paced, multidisciplinary environment.
• Understanding of software development best practices, including coding standards, code reviews, source control and test automation.
• Experience with robotics, autonomous systems or real-time perception applications is strongly preferred.

Required skills

• Proficiency in Python and deep learning frameworks such as PyTorch and/or JAX.
• Hands-on experience training models such as VLMs, ViTs and/or CNNs.
• Familiarity with classical computer vision techniques (e.g., OpenCV).
• Knowledge of MLOps practices (model versioning, CI/CD for ML) is a plus.
• Experience with camera geometry, 3D reconstruction or GPU programming (CUDA, Triton) is a plus.