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# Senior AI Automation Engineer, Data Annotation Services

- **Company:** Caterpillar
- **Location:** Irving, TX, United States
- **Experience:** Expert
- **Salary:** $112,710.0 - $183,140.0
- **Contract:** Permanent contract
- **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Computer Vision, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Software Engineering, Software Systems, Pytorch, Delivery Pipeline, Kubernetes, Information Technology, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, Lidar, Data Pipelines, Automation Anywhere, Docker
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-ai-automation-engineer-data-annotation-services-irving-tx--eeed35de-a675-4cdf-8dc8-cff0a8589219

## About the Role

Automation Engineering, Artificial Intelligence (AI), Training Data Sets, Caterpillar Equipment, Problem Solving Skills, Artificial Intelligence (AI), Vehicle Fleets, Computer Architecture, Continuous Improvement, Performance Management, * 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.

Preferred Qualifications

 * 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.