AI Automation Engineer, Data Annotation Services

Caterpillar Inc.•Irving, TX

3d•$97,530 - $158,480•Onsite

About The Position

Caterpillar Inc. is seeking an AI Automation Engineer to join their global team focused on building stronger, more sustainable communities through technology. This role is part of the Cat Technology initiative, which aims to solve customer challenges by creating an intelligence layer connecting machines, data, and people for safer, more productive, and sustainable jobsites. The engineer will work with a unique data foundation from over 1.6 million connected assets, enabling the development of AI models, edge computing architectures, and software systems. The position is at the intersection of the physical and digital worlds, contributing to intelligent systems that allow machines to perceive their environment, make informed decisions, and support safer, more productive operations, particularly in the field of construction autonomy. The AI Automation Engineer will develop annotation automation solutions for training data used in robotics, autonomy, computer vision, and Vision-Language-Action (VLA) systems within a scrum team. This role combines software engineering, machine learning, and data engineering to build automated annotation and captioning capabilities for heavy equipment and construction environments, utilizing technologies like NVIDIA Cosmos Curator and Cosmos Reason, and developing Caterpillar-specific AI models for automated labeling, captioning, and quality assurance. It is a hands-on technical role focused on creating scalable production solutions for complex AI and data challenges.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Robotics, or a related field.
Experience developing production-grade software solutions using Python, modern software engineering practices and containerization platforms (e.g. Docker, Kubernetes)
Experience designing and implementing distributed systems, APIs, and data processing pipelines.
Experience training, fine-tuning, or deploying machine learning models.
Strong problem-solving skills and ability to work across multiple technical disciplines.
Experience generating and managing camera and LiDAR sensor datasets for perception or machine learning applications, including data collection pipeline design and ground truth generation.
Experience in data annotation and quality assurance for autonomous systems or computer vision projects, with demonstrated ability to define annotation guidelines, identify labeling defects, and drive measurable improvements in dataset accuracy.
Experience using annotation and dataset management tools such as Labelbox, Supervisely, RoboFlow or similar toolchains.
Experience using machine learning frameworks and training tools such as PyTorch, TensorFlow, ONNX, Weights & Biases, MLflow or similar frameworks.

Nice To Haves

Experience with computer vision, robotics, autonomy, Physical AI, or multimodal AI systems.
Experience with AI-assisted annotation, auto-labeling, or machine learning data pipelines.
Experience training or fine-tuning foundation models, vision models, or multimodal models.
Experience with NVIDIA Cosmos Curator, Cosmos Reason, or similar AI automation platforms.
Experience with Vision-Language-Action (VLA) datasets and workflows.
Experience with sensor data such as cameras, LiDAR, radar, or autonomous machine datasets.
Experience with cloud platforms, MLOps, and machine learning deployment pipelines.
Experience building human-in-the-loop AI workflows and quality automation systems.

Responsibilities

Develop and deploy automated labeling and captioning solutions for perception and VLA datasets.
Train, fine-tune, and evaluate AI models to support auto-labeling, auto-captioning, and annotation quality automation.
Build data pipelines and workflows that move datasets through automated labeling, human review, quality validation, and dataset publication.
Implement and extend platforms such as NVIDIA Cosmos Curator, Cosmos Reason, and other emerging AI automation technologies.
Develop solutions that integrate Caterpillar data systems with external annotation providers and human-in-the-loop workflows.
Ensure reliability, scalability, observability, and operational excellence across annotation automation services.