Senior Annotation & Quality Manager

About the role

Caterpillar is seeking a Data Annotations & Quality Manager to lead the teams responsible for producing, automating, and validating the datasets that power Physical AI, autonomy, robotics, and machine learning systems. This leader will oversee three critical functions: Data Annotation, AI Automation Engineering, and Data Quality Engineering.

Responsibilities

• Lead Data Annotation Operations: Manage teams responsible for labeling image, video, LiDAR, radar, telemetry, geospatial, and other machine-generated data.
• Establish scalable annotation processes, standards, and quality controls.
• Own annotation throughput, quality, cost, and delivery metrics.
• Drive continuous improvement of annotation workflows, instructions, and quality assurance practices.
• Lead AI-Powered Annotation Automation: Build and lead teams developing auto-labeling, pre-labeling, active learning, and human-in-the-loop annotation solutions.
• Establish strategies for maximizing automation while maintaining quality and trustworthiness.
• Lead Data Quality Engineering: Establish the enterprise data quality strategy for AI training datasets.
• Define data quality standards, acceptance criteria, and service-level objectives.
• Implement quality monitoring, anomaly detection, validation rules, and observability capabilities across the data lake.
• Deliver Trusted AI Training Data: Define data readiness criteria for model training and evaluation.
• Establish governance for annotation standards, ontologies, labeling guidelines, and dataset versioning.
• Build and Develop High-Performing Teams: Recruit, develop, and mentor annotation leaders, automation engineers, and data quality engineers.

Requirements

• Leadership Experience leading technical and operational teams in data, AI, machine learning, analytics, or software engineering environments.
• Data-Centric AI Expertise: Strong understanding of how training data impacts machine learning and AI performance.
• Data Quality & Governance: Experience establishing data quality standards, monitoring frameworks, and governance processes.
• Software & Automation: Experience working with engineering teams building scalable software systems.
• Communication & Influence: Ability to communicate effectively with engineering, product, AI, research, and business leaders.

Qualifications

Top candidates will have experience supporting Physical AI, autonomy, robotics, simulation, perception, or digital twin systems. They will also have experience with multimodal data, including image, video, LiDAR, radar, GPS, IMU, telemetry, and geospatial data.

Skills

• Experience with annotation workflows, ontology management, or dataset development.
• Experience with automation, machine learning workflows, and human-in-the-loop systems.
• Familiarity with active learning, auto-labeling, synthetic data, and human-in-the-loop AI workflows.
• Experience developing data quality metrics such as completeness, consistency, accuracy, coverage, bias, and drift detection.

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

Pay

The pay range for this position is $159,120.00 - $258,570.00. Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job-related knowledge, skills, individual performance, and experience.

Schedule

This position requires the candidate to work full-time at the Irving, Texas office. Domestic relocation assistance is available for this position. Visa sponsorship is available with this position.