Senior AI Automation Engineer, Data Annotation Services

Role Overview

As a Senior AI Automation Engineer, you will develop annotation automation solutions used to create training data for robotics, autonomy, computer vision, and Vision-Language-Action (VLA) systems with a scrum team. You will help deploy and extend technologies such as NVIDIA Cosmos Curator and Cosmos Reason while also developing Caterpillar-specific AI models that enable automated labeling, automated captioning, and AI-driven quality assurance.

What You Will Do

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.

Why It Might Be a Fit

This role combines software engineering, machine learning, and data engineering to build automated annotation and captioning capabilities for real-world heavy equipment and construction environments. You will help design and deliver intelligent systems that enable machines to perceive their environment, make informed decisions, and support safer, more productive operations.

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.
• 2+ years of experience generating and managing camera and LiDAR sensor datasets for perception or machine learning applications, including data collection pipeline design and ground truth generation.
• 1+ years of 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.

Benefits

• Medical, dental, and vision benefits
• Paid time off plan (Vacation, Holidays, Volunteer, etc.)
• 401(k) savings plans
• Health Savings Account (HSA)
• Flexible Spending Accounts (FSAs)
• Health Lifestyle Programs
• Employee Assistance Program
• Voluntary Benefits and Employee Discounts
• Career Development
• Incentive bonus
• Disability benefits
• Life Insurance
• Parental leave
• Adoption benefits
• Tuition Reimbursement