Google Cloud Machine Learning Engineer
About the Role
Google Cloud Consulting Professional Services team assists customers in their cloud journey, helping businesses thrive through technological innovation.
Location & Application Details
- Application Window: Open until at least 05/09/2025, subject to business needs.
- Preferred Locations: Atlanta, GA; Chicago, IL; Austin, TX; Boulder, CO; Toronto, ON, Canada.
Minimum Qualifications
- Bachelor's degree in Computer Science or equivalent practical experience.
- 6 years of experience in building machine learning solutions and supporting technical customers.
- Experience designing cloud enterprise solutions and supporting customer projects.
- Proficient in programming languages such as Python, Java, Go, C, or C++, including knowledge of data structures, algorithms, and software design.
Preferred Qualifications
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost).
- Knowledge of recommendation engines, data pipelines, or distributed machine learning.
- Understanding of data warehousing concepts and related tools (e.g., Apache Beam, Hadoop, Spark, Hive).
- Practical knowledge of production machine learning system concerns.
Job Responsibilities
- Act as a trusted technical advisor to customers.
- Coach customers on ML systems feature extraction, validation, monitoring, and management.
- Collaborate with customers, partners, and Google product teams to deliver tailored production solutions.
- Create tutorials, blog posts, and sample codes based on best practices.
- Travel up to 30% for meetings, reviews, and onsite activities.
Compensation & Benefits
- Base Salary Range (US): $147,000-$216,000
- Plus bonus, equity, and benefits.
- Salary depends on location, experience, skills, and education.
Commitment to Diversity
Google is an equal opportunity employer, committed to creating an inclusive environment regardless of race, religion, gender, or other characteristics.
Responsibilities
- Provide technical expertise and guidance.
- Assist in feature engineering, data validation, monitoring, and management.
- Support deployment, troubleshooting, and monitoring of ML solutions.
- Contribute to community knowledge through blogs, tutorials, and code samples.
- Travel as needed for customer engagement.
Additional Information
- Legal background checks and accommodations available.