Career Area:
Technology, Digital and Data
Job Description:
Job Summary:
We are seeking a highly experienced Principal Software Engineer to define and lead the system design of annotation and dataset quality systems that enable machine learning and AI for physical systems for autonomy.
This role is responsible for designing the end-to-end system design for how raw sensor data is transformed into high-quality labeled datasets, ensuring that training data is accurate, consistent, and aligned to model needs.
The Principal Software Engineer will act as the technical authority for annotation and dataset quality, defining system design, standards, and engineering patterns that annotation and dataset quality engineering teams will implement and scale.
This is a hands-on technical role, focused on solving complex challenges such as labeling consistency, ontology design, quality validation, human-in-the-loop workflows, and continuous dataset improvement.
Success in this role requires expertise in data-centric AI, annotation systems, and quality engineering, along with the ability to operate in ambiguous environments where requirements evolve based on model performance and real-world behavior.
What You Will Do:
Data Quality Architecture & Standards
- Define and establish data quality frameworks, including validation rules, scoring models, and acceptance criteria.
- Design systems for label validation, consistency checking, and anomaly detection at scale.
- Define metrics that matter (e.g., consistency, agreement, completeness, fitness for model use).
- Establish standards for dataset readiness and production acceptance for ML systems.
- Design approaches for continuous data quality monitoring and improvement.
- Establish standards for auditability and dataset governance.
Quality Feedback Loops (Data-Centric AI)
- Define how model performance feeds back into annotation prioritization and strategy.
- Design systems for active learning, error mining, and targeted data improvement.
- Establish mechanisms to continuously improve datasets based on real-world model behavior.
Technical Leadership & Influence
- Provide design direction to annotation and dataset quality engineering teams.
- Review and guide detailed designs to ensure alignment with system-wide architecture.
- Partner with ML, autonomy, and product teams to ensure data quality drives system performance.
- Act as the technical authority for annotation and dataset quality across the organization.
Software Engineering Excellence
- Lead development efforts using Python and/or Java in enterprise-scale environments.
- Champion SDLC discipline including CI/CD, automated testing, infrastructure as code, code quality, release management, and operational maturity.
- Establish engineering practices supporting reliability, observability, maintainability, and platform stability.
- Participate in hands-on development, prototyping, troubleshooting, and performance tuning of critical platform components.
- Drive modernization initiatives and continuous improvement of engineering processes and platform capabilities.
- Promote iterative engineering practices that balance rapid innovation with production-grade engineering discipline.
Agile & Cross-Team Collaboration
- Work closely with Product Management, Data Engineering, Annotation Engineering, Platform Engineering, and DevOps teams.
- Translate business and platform objectives into actionable technical roadmaps for scrum teams.
- Provide technical leadership across multiple agile teams and ensure alignment to architectural strategy.
- Facilitate technical design reviews, sprint planning, backlog refinement, dependency management, and engineering governance activities.
- Influence engineering culture by promoting collaboration, accountability, adaptability, and engineering rigor.
What You Will Have:
- Decision Making and Critical Thinking: Extensive knowledge of the decision-making process and associated tools and techniques; ability to accurately analyze situations and reach productive decisions based on informed judgment.
- Effective Communications: Superior understanding of effective communication concepts, tools and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through the application of appropriate communication behaviors.
- Software Development: Expert knowledge of software development tools and activities; ability to produce software products or systems in line with product requirements.
- Software Development Life Cycle: Expert knowledge of software development life cycle; ability to use a structured methodology for delivering and managing new or enhanced software products to the marketplace.
- Software Integration Engineering: Extensive knowledge of software integration processes and functions; ability to design, develop and maintain interfaces and linkage to alternative platforms and software packages.
- Software Product Design/Architecture: Extensive knowledge of software product design; ability to convert business requirements into the software product design.
- Software Product Technical Knowledge: Extensive knowledge of technical aspects of a software products; ability to design, configure and integrate technical aspects of software products.
- Software Product Testing: Extensive knowledge of software product testing; ability to design, plan, and execute testing strategies and tactics to ensure software product quality and adherence to stated requirements.
Top Candidates Will Have:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Engineering, or related field.
- 10+ years of software engineering experience with significant experience in principal, staff, or lead-level technical leadership roles.
- Expert-level proficiency in Python and/or Java.
- Expertise in computer vision, sensor-based systems, or ML-driven products.
- Strong experience designing annotation platforms, labeling systems, or data quality frameworks
- Strong understanding of data-centric AI and training data lifecycle management.
- Experience defining label ontologies, annotation guidelines, and quality standards.
- Experience building or scaling human-in-the-loop systems.
- Strong understanding of data quality metrics and their impact on model performance.
- Experience connecting model failures back to data issues and driving improvements.
- Proven ability to lead architectural direction across multiple teams.
- Deep expertise in system design, distributed systems, and large-scale cloud-native architectures.
- Strong experience designing and implementing streaming and batch data processing systems at enterprise scale.
- Hands-on experience with AWS cloud services and architecture patterns; experience with Azure or GCP also valued.
- Experience leading technical strategy across multiple engineering teams in agile environments.
- Demonstrated success operating effectively in highly ambiguous or rapidly evolving technical environments.
- Strong comfort level with experimentation, prototyping, and iterative architecture refinement.
- Ability to make sound technical decisions with incomplete information and evolving constraints.
Preferred Qualifications
- Experience supporting AI/ML, autonomous systems, computer vision, robotics, or advanced analytics platforms.
- Experience with multimodal data (LiDAR + image + telemetry) annotation strategies.
- Familiarity with annotation tools or platforms (CVAT, Labelbox, SuperAnnotate, or similar).
- Experience with auto-labeling, active learning, or hybrid annotation systems.
- Experience leading or influencing annotation operations at scale (internal or vendor-based).
ADDITIONAL DETAILS
- This position requires the candidate to be based in Irving, TX (Dallas)
- Domestic relocation assistance is available for this position.
- Visa sponsorship is available for 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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