Senior Data Quality Engineer, Data Quality Services

Career Area:
Technology, Digital and Data

Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

Help Build the Future of Caterpillar –

At Caterpillar, technology always has a purpose, which is to solve our customers’ toughest challenges. Through Cat Technology, we are solving problems by building the intelligence layer that connects machines, data, and people to make jobsites safer, more productive, and more sustainable. By combining deep domain expertise in physical systems with software, connectivity, autonomy, and AI, we deliver solutions that work in the real world—on real jobsites, at global scale.

You’ll build and deploy against one of the most unique data foundations—over 1.6 million connected assets generating real-world data daily. These data and platform capabilities are enabling the development of AI models, edge computing architectures, and software systems that scale across fleets, products, and industries. The result will be a new generation of machines that continuously learn, improve, and deliver performance at scale.

Be Part of What’s Next in Autonomous Construction Sites

Construction autonomy is one of the most complex challenges in applied AI, and at Caterpillar, advancements in physical AI, simulation, sensing, and edge computing are turning things that once felt impossible—intelligent machines operating in dynamic jobsites—into reality.

Our connected ecosystem brings together massive volumes of high-quality data to create a foundation where engineers like you can build and deploy against.

If this work motivates you, we invite you to join our team. In these roles, you’ll work at the intersection of the physical and digital worlds. You’ll help design and deliver intelligent systems that enable machines to perceive their environment, make informed decisions, and support safer, more productive operations.

Apply today to build the new era of construction autonomy at Caterpillar.

Job Summary

We are seeking a Senior Data Quality Engineer to define, measure, and automate the quality of the training and validation data used for robotics, autonomy, computer vision, and Vision-Language-Action (VLA) systems with a scrum team.

This role combines data engineering, machine learning, and quality engineering to build the quality gates, metrics, and validation tooling that ensure every dataset—from raw camera and LiDAR captures to auto-labeled annotations and captions—meets the accuracy, consistency, and coverage standards required to train and evaluate Caterpillar autonomy models. You will partner closely with AI Automation, Data Engineering, perception/ML model teams, and external annotation providers, leveraging technologies such as NVIDIA Cosmos Curator and Cosmos Reason alongside Caterpillar-specific AI models to scale AI-driven quality assurance.

This is a hands-on technical role focused on making data quality measurable, automated, and continuously improving at production scale.

What You'll Do

- Define data quality standards, acceptance criteria, and annotation guidelines for sensor data, labels, and captions used in perception and VLA datasets.

- Build automated quality gates that validate data at every stage, from ingestion and labeling through dataset publication.

- Develop and deploy AI-driven quality checks such as label-noise detection, consensus scoring, and caption verification using vision-language models (e.g., Cosmos Reason).

- Define and track dataset quality KPIs such as label accuracy, inter-annotator agreement, and rework rate, and share results through dashboards and reports.

- Audit internal and vendor annotations using gold datasets and statistical sampling, and manage annotation providers through scorecards, feedback loops, and SLAs.

- Analyze dataset coverage and gaps, trace model failures back to data issues, and ensure dataset lineage, versioning, and governance.

What Makes This Role Unique

Most data quality practices were built for structured business data—not for multimodal sensor data captured from heavy equipment operating on dynamic jobsites.

In this role, you'll define what "good data" means for Caterpillar's autonomy and Physical AI programs. You'll work across computer vision, LiDAR, multimodal AI, and Vision-Language-Action datasets, directly influencing model performance and machine safety by ensuring the data that trains intelligent machines is accurate, consistent, and representative of real-world operating conditions.

Basic Qualifications

- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Robotics, or a related field.

- 3+ years of experience developing production-grade software using Python and SQL, modern software engineering practices, and containerization platforms (e.g. Docker, Kubernetes).

- 3+ years of experience designing and implementing data pipelines, APIs, and distributed data processing systems.

- 3+ years of experience building data validation frameworks and automated quality checks for large-scale datasets.

- Strong understanding of statistics and sampling methods used to audit and measure data quality.

- 3+ years of experience managing Camera and LiDAR sensor datasets for autonomy or computer vision, including ground truth generation and annotation quality assurance.

- Demonstrated ability to define annotation guidelines, identify labeling defects, and drive measurable improvements in dataset accuracy.

- 3+ years of experience using annotation and dataset management tools (e.g. Labelbox, CVAT, FiftyOne) and machine learning frameworks (e.g. PyTorch, MLflow).

- Strong problem-solving and communication skills, with the ability to work across technical teams and external vendors.

Preferred Qualifications

- Experience with computer vision, robotics, autonomy, Physical AI, or multimodal AI systems.

- Experience with AI-assisted quality techniques such as label-noise detection, active learning, or consensus-based review.

- Experience evaluating vision-language model outputs or working with Vision-Language-Action (VLA) datasets.

- Experience with NVIDIA Cosmos Curator, Cosmos Reason, or similar AI data curation platforms.

- Experience with data lineage, dataset versioning, and workflow orchestration tools (e.g. DVC, Airflow).

- Experience with cloud platforms, MLOps, and machine learning deployment pipelines.

- Experience managing vendor quality programs, including scorecards and SLAs.

Additional Details:

- This position requires the candidate to work full-time at the Irving, TX office (Dallas)

- Domestic relocation assistance is available for this position.

- Visa sponsorship is available with this position.

Summary Pay Range:

$112,710.00 - $183,140.00

Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job-related knowledge, skills, individual performance and experience. Please note that salary is only one component of total compensation at Caterpillar.

Benefits:

Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.

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Medical, dental, and vision benefits*

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Paid time off plan (Vacation, Holidays, Volunteer, etc.)*