Develop machine learning models for automated root cause analysis of validation and test failures
Build predictive analytics to support failure detection, forecasting, and risk identification
Design pattern-recognition techniques to identify failure signatures in historical validation data
Develop dashboards and reporting tools that enable data-driven validation decisions
Implement AI-driven test selection and prioritization approaches based on code change risk
Develop methods to identify test coverage gaps, overlaps, and inefficiencies
Contribute to optimization solutions that reduce test execution time while maintaining quality
Develop AI-powered test generation solutions using requirements and code change data
Build adaptive test execution capabilities informed by historical performance data
Assist with integrating LLM-based capabilities into validation workflows where appropriate
Work with firmware, hardware, and system teams to understand validation challenges
Collaborate with validation engineers to translate domain knowledge into ML features
Partner with platform and infrastructure teams to deploy and maintain AI/ML solutions
Support adoption of AI tools through documentation, training, and team enablement

4+ years of industry experience with a Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or a related technical field
5+ years of software development experience, primarily using Python
Solid understanding of machine learning fundamentals, including model development, evaluation, and feature engineering
Experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, or similar
Experience building and deploying ML solutions in production or large-scale environments

Choice of medical, dental and vision plans
Benefit programs that help protect your income if you are unable to work due to illness or injury
Paid family leave
Robust paid time-off program
Paid holidays

Senior AI/ML Engineer, Validation Strategy, Test Architecture

Key skills