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Software Engineer III, AI/ML

Google

Kirkland, Washington, United StatesOn Site

Original Job Summary

About Software Engineer III, AI/ML

Google's Software Engineer III, AI/ML develops cutting-edge technologies for Google Cloud. The engineer will work on a critical project with opportunities to switch teams and projects as business needs evolve.

Minimum Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year with an advanced degree.
  • 1 year of experience in Speech/audio, reinforcement learning, ML infrastructure, or another ML field.
  • 1 year of experience with ML infrastructure including model deployment, evaluation, optimization, data processing, or debugging.

Preferred Qualifications

  • Master's degree or PhD in Computer Science or related fields.
  • 2 years of experience with data structures or algorithms.
  • Experience developing accessible technologies.

About the Role

Software Engineer III, AI/ML at Google will contribute to next-generation technology development, focusing not only on code development but also on design reviews, collaboration, and system troubleshooting. Responsibilities include writing development code, debugging product issues, contributing to documentation, and implementing ML-specific solutions.

Responsibilities

  • Write product or system development code.
  • Collaborate with peers and stakeholders through design and code reviews.
  • Contribute to and adapt documentation based on updates and feedback.
  • Triage, debug, and resolve product or system issues.
  • Implement ML solutions using specialized areas and ML infrastructure.

Key Skills/Competency

  • Software Development
  • AI/ML
  • Cloud Computing
  • Model Deployment
  • Debugging
  • Data Processing
  • Algorithms
  • Distributed Systems
  • Collaboration
  • Technical Documentation

How to Get Hired at Google

🎯 Tips for Getting Hired

  • Research Google Cloud: Understand its culture, products, and technology.
  • Customize your resume: Highlight relevant AI/ML projects and skills.
  • Prepare for technical interviews: Review data structures and algorithms.
  • Practice behavioral questions: Emphasize teamwork and problem solving.

📝 Interview Preparation Advice

Technical Preparation

Review ML algorithms and data processing.
Practice coding in multiple languages.
Study distributed systems and cloud architecture.
Brush up on model deployment and debugging.

Behavioral Questions

Describe a challenging team project.
Explain your problem-solving process.
Discuss time management under pressure.
Share an experience with cross-team collaboration.