Career Area:Technology, Digital and Data
Job Description:Role:
We are 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 - Teams responsible for manual labeling and quality assurance of multimodal sensor data.
- AI Automation Engineering - Engineers who build and maintain auto-labeling, AI-assisted annotation, and human-in-the-loop systems to improve scalability and efficiency.
- Data Quality Engineering - Engineers responsible for measuring, monitoring, and enforcing data quality standards across the data lake to ensure datasets remain fit for AI training and production use.
The successful candidate will build and lead a high-performing organization that transforms raw sensor and operational data into trusted, high-quality datasets that enable machine learning, simulation, digital twin, and autonomy initiatives. This role requires a combination of people leadership, operational excellence, data-centric AI expertise, and quality engineering discipline.
What You Will DoLead 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.
- Partners with AI and software engineering teams align annotation priorities with model development needs.
Lead AI-Powered Annotation Automation
- Build and lead teams developing auto-labeling, pre-labeling, active learning, and human-in-the-loop annotation solutions.
- Drive adoption of AI-assisted labeling tools to improve annotation speed and reduce costs.
- Establish strategies for maximizing automation while maintaining quality and trustworthiness.
- Define success metrics for automation effectiveness, precision, recall, and reviewer effort reduction.
- Collaborate with machine learning teams to incorporate model feedback into annotation workflows.
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.
- Develop quality scorecards and dashboards that measure dataset health over time.
- Detect and respond to data degradation, schema drift, annotation drift, missing data, and quality regressions.
- Ensure training datasets maintain fitness for intended AI use cases.
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.
- Drive consistency across datasets produced by internal teams and external vendors.
- Partner with data engineering teams to improve upstream data quality before annotation begins.
- Partner with machine learning teams to understand model failures and prioritize data improvements.
Build and Develop High-Performing Teams
- Recruit, develop, and mentor annotation leaders, automation engineers, and data quality engineers.
- Establish career paths and skills development across all disciplines.
- Foster a culture focused on quality, innovation, ownership, and continuous improvement.
- Manage budgets, staffing plans, vendor relationships, and operational priorities.
What You Will HaveLeadership
- Experience leading technical and operational teams in data, AI, machine learning, analytics, or software engineering environments.
- Track record of building and scaling high-performing teams.
Data-Centric AI Expertise
- Strong understanding of how training data impacts machine learning and AI performance.
- Experience with annotation workflows, ontology management, or dataset development.
Data Quality & Governance
- Experience establishing data quality standards, monitoring frameworks, and governance processes.
- Understanding data observability, data validation, and quality measurement techniques.
Software & Automation
- Experience working with engineering teams building scalable software systems.
- Familiarity with automation, machine learning workflows, and human-in-the-loop systems.
- Communication & Influence
- Ability to communicate effectively with engineering, product, AI, research, and business leaders.
- Strong stakeholder management and decision-making skills.
Top Candidates Will Have- Experience supporting Physical AI, autonomy, robotics, simulation, perception, or digital twin systems.
- Experience with multimodal data including image, video, LiDAR, radar, GPS, IMU, telemetry, and geospatial data.
- Experience leading annotation programs involving internal teams, vendors, and AI-assisted labeling systems.
- Experience building data quality monitoring platforms and observability solutions.
- 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.
- Experience with cloud-scale data platforms and large data lakes.
- Experience managing geographically distributed teams.
Additional Details:- 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
Summary Pay Range:$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. 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.
- 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
* These benefits also apply to part-time employees
Posting Dates:Any offer of employment is conditioned upon the successful completion of a drug screen.
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