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Software Engineer III AI ML Google Cloud Business Platforms

Google

Mountain View, California, United StatesOn Site

Original Job Summary

About the Role

The Software Engineer III AI ML Google Cloud Business Platforms role at Google demands expertise in software development along with specialized experience in AI/ML. This position offers an opportunity to work on critical projects that drive next-generation technologies across billions of users worldwide.

Minimum Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of software development experience 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 specialization.
  • 1 year of experience with ML infrastructure including model deployment, evaluation, optimization, data processing and debugging.

Preferred Qualifications

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

Responsibilities

  • Write product or system development code.
  • Collaborate with peers and stakeholders via design and code reviews.
  • Contribute to documentation and adapt educational content.
  • Triage issues by debugging and resolving product or system problems.
  • Implement solutions in specialized ML areas and utilize ML infrastructure.

Compensation & Benefits

The US base salary range for this full-time role is $141,000-$202,000 plus bonus, equity, and benefits. Note that these figures represent the base salary portion only.

Key skills/competency

  • Software Development
  • AI
  • Machine Learning
  • Google Cloud
  • ML Infrastructure
  • Debugging
  • Problem Solving
  • Code Reviews
  • Data Processing
  • Collaboration

How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your coding and ML experience.
  • Study Google technologies: Focus on AI and cloud innovations.
  • Prepare coding challenges: Practice algorithm and data structure problems.
  • Show collaborative experience: Highlight teamwork and code review practices.

📝 Interview Preparation Advice

Technical Preparation

Review ML infrastructure components
Practice coding challenges in multiple languages
Study algorithms and data structure basics
Build small projects using ML models

Behavioral Questions

Discuss past teamwork experiences
Explain problem solving in projects
Show examples of handling challenges
Describe adaptability during change