Job Description

We are seeking a highly skilled and visionary AI Engineer/Lead. This position is pivotal to the Control Tower and Field Quality organization, driving the development, validation, and evolution of AI/ML tools that support warranty analytics, customer feedback, and quality improvement initiatives. The ideal candidate will possess deep expertise in Control Tower processes, warranty lifecycle management, and advanced data modeling using Palantir Foundry tools.

Key Responsibilities:

• Lead the modeling, creation, enhancement, and validation of AI/ML applications for Field Quality and Control Tower initiatives
• Collaborate cross-functionally with engineering, warranty, and customer experience teams to align AI tools with business needs
• Drive the evolution of the AI roadmap for Quality, identifying opportunities for innovation and scalability
• Translate complex warranty and customer feedback data into actionable insights using Palantir tools such as My Customer Voice, Quiver, and Complex Foundry Analysis
• Ensure robust testing and validation of AI/ML models to meet performance, accuracy, and reliability standards
• Support continuous improvement of existing AI applications through iterative development and stakeholder feedback
• Mentor junior engineers and contribute to a culture of technical excellence and innovation

Qualifications

Basic Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
• 5+ years of experience in AI/ML modeling, testing, and validation, preferably in automotive or manufacturing quality domains
• Strong understanding of Control Tower operations and end-to-end warranty processes
• Proven experience with Palantir Foundry tools, including My Customer Voice, Quiver, and complex analytical workflows
• Proficiency in Python, SQL, and data visualization tools
• Ability to envision, adapt, and enhance AI strategies aligned with evolving business goals
• Excellent communication and stakeholder engagement skills

Preferred Qualifications:

• Experience in deploying AI/ML models in production environments
• Familiarity with cloud platforms and MLOps practices
• Background in field quality analytics or customer satisfaction metrics
• Prior leadership or mentoring experience in technical teams