Strategic Cloud Engineer Artificial Intelligence @ Google
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Minimum Qualifications
Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience. 6 years of experience in building Machine Learning or Data Science solutions. Experience with writing software in Python, Scala, R. Proficient in data structures, algorithms, and software design. Ability to travel up to 30% of the time as required.
Preferred Qualifications
Experience in working with recommendation engines, data pipelines, or distributed machine learning with data analytics, data visualization techniques and software, and deep learning frameworks. Familiarity with Data Science techniques and knowledge of data warehousing concepts including ETL/ELT processes, as well as cloud computing principles like virtualization and multi-tenant infrastructures. Excellent communication skills are required.
About the Job
The Google Cloud team assists companies, schools, and governments in making a seamless switch to Google products. In the role of Strategic Cloud Engineer Artificial Intelligence, you will listen to customers, solve technical issues, and work closely with web developers, systems administrators, and global customers. Your efforts will be crucial for Google Cloud’s growth and in helping businesses innovate using cutting-edge technology.
Responsibilities
- Deliver big data and machine learning solutions and solve customer technical tests.
- Act as a trusted technical advisor to Google’s customers.
- Identify product feature gaps and collaborate with Product Managers and Engineers.
- Create recommendations, tutorials, blog articles, and technical presentations for diverse audiences.
- Drive AI engagement through thought leadership.
Key skills/competency
- Machine Learning
- Data Science
- Cloud Computing
- Python
- Scala
- Algorithms
- Data Pipelines
- Deep Learning
- ETL
- Technical Presentation
How to Get Hired at Google
🎯 Tips for Getting Hired
- Customize your resume: Tailor technical skills to job description.
- Research Google: Understand their culture and products.
- Prepare examples: Demonstrate ML and cloud projects.
- Practice interviews: Sharpen technical and scenario questions.