Machine Learning Engineer
Core
Designing, training, deploying, and optimizing machine learning models for advanced robotics applications, specifically focusing on perception, scene understanding, and decision-making in industrial environments.
Role type
Applied Scientist / ML Engineer (Robotics)
Builds
Scalable ML systems, neural network architectures, and data pipelines for industrial robotics platforms.
Domain
Industrial Automation / Robotics / Computer Vision
Deliverable
production ML models
Required skills
Deep learning, object detection, segmentation, pose estimation, scene understanding, neural network architecture design, scalable training and inference pipelines, synthetic data generation, fine-tuning, model optimization, real-time system integration.
Preferred skills
Foundation models, generative AI approaches, scalable ML infrastructure.
Technologies
Deep learning frameworks, robotics control systems, data pipeline tools.
Responsibilities
Develop robust neural network architectures for object detection, segmentation, and pose estimation; build scalable training and inference pipelines; design and maintain data pipelines for collection, ingestion, curation, and synthetic data generation; integrate ML systems into broader robotics pipelines.
Seniority
Mid-to-Senior, hands-on IC