Cloud Developer I AI/ML Professional Services
@ Google

Toronto, ON
$150,000
On Site
Full Time
Posted 21 days ago

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Job Details

About Google Cloud Developer I AI/ML Professional Services

The application window remains open until at least September 25, 2025, with business needs potentially altering the timeline. Applicants can indicate their preferred working location from Austin, TX; Toronto, ON; Atlanta, GA; Boulder, CO; or Chicago, IL.

Minimum Qualifications

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 3 years building machine learning solutions with technical customers.
  • Experience designing cloud enterprise solutions and completing customer projects.
  • Proficiency in programming languages such as Python, Java, Go, C, or C++.

Preferred Qualifications

  • Experience with recommendation engines, data pipelines, or distributed ML.
  • Knowledge of deep learning frameworks like TensorFlow, PyTorch, or XGBoost.
  • Understanding data warehousing concepts and ETL/ELT processes using tools like Apache Beam, Hadoop, Spark, etc.
  • Familiarity with production ML systems challenges.

About the Role

As a Cloud Developer I AI/ML Professional Services at Google, you will design and implement machine learning solutions for customers leveraging Google technologies including TensorFlow, DataFlow, and Vertex AI. This role involves customer engagements, workshops, technical reviews, and on-site deployments with up to 30% travel. You will advise customers, deliver best practices, and work closely with product teams and partners.

Compensation & Benefits

The US base salary range is $123,000-$176,000 plus bonus, equity, and benefits. Specific salary will depend on location and candidate qualifications. Additional benefits are available as detailed on Google’s benefits page.

Key Skills/Competency

  • Cloud
  • Machine Learning
  • Python
  • TensorFlow
  • DataFlow
  • Vertex AI
  • Cloud Solutions
  • Customer Engagement
  • Deep Learning
  • Data Warehousing
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How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Highlight ML and cloud experience.
  • Research Google: Understand culture and technical needs.
  • Prepare projects: Detail completed cloud implementations.
  • Practice interviews: Focus on ML algorithms and design.

📝 Interview Preparation Advice

Technical Preparation

Review cloud architecture fundamentals.
Practice ML algorithm coding challenges.
Study TensorFlow and Vertex AI tutorials.
Understand data pipeline design concepts.

Behavioral Questions

Describe a complex ML project you handled.
Explain how you manage client expectations.
Share an experience improving system performance.
Discuss teamwork in challenging deployments.

Frequently Asked Questions