Pixel Test Engineer — AI/ML Infra & Automation

Google Inc.; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google Mountain View, CA is seeking a Software Engineer for Pixel Test Engineering/AI Application to help build and own cutting-edge cross-device test infrastructure. You will drive faster release cycles and higher quality software by leveraging ML and AI-powered automation across platforms.

The role emphasizes collaboration, code development, and contributing to model optimization, with in-person interviews commonly required.

Qualifications

• Bachelor’s degree or equivalent practical experience in CS or related field.
• 2 years of software development experience.
• Experience with ML infrastructure, model deployment, evaluation, or data processing.

Responsibilities

• Write product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

Skills

ML infrastructure

Reinforcement learning

Speech/audio

Model deployment

Data processing

Model evaluation

Debugging

Optimization

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in Computer Science or related fields

Job description

Google Mountain View, CA is seeking a Software Engineer for Pixel Test Engineering/AI Application to help build and own cutting-edge cross-device test infrastructure. You will drive faster release cycles and higher quality software by leveraging ML and AI-powered automation across platforms.

The role emphasizes collaboration, code development, and contributing to model optimization, with in-person interviews commonly required.