Cloud Engineer, Artificial Intelligence
Job Overview
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Job Description
About the Role: Cloud Engineer, Artificial Intelligence
As a Cloud Engineer, Artificial Intelligence at Google, you will be instrumental in guiding customers through their adoption of Google Cloud's machine learning (ML) product suite. This role involves designing and implementing robust machine learning solutions tailored to customer use cases, leveraging Google's cutting-edge technologies. You will proactively identify opportunities for businesses to transform using machine learning, traveling to customer sites to deploy solutions and conduct educational workshops.
Key Responsibilities
- Deliver effective big data and machine learning solutions, actively resolving technical customer issues.
- Act as a trusted technical advisor to Google’s customers, providing expert guidance.
- Identify new product features and feature gaps, offer insights on existing product challenges, and collaborate closely with Product Managers and Engineers to shape the Google Cloud Platform roadmap.
- Produce and deliver best practice recommendations, insightful tutorials, informative blog articles, and compelling technical presentations, adapting content for diverse business and technical stakeholders.
Minimum Qualifications
- Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
- Demonstrated experience in building machine learning or data science solutions.
- Proficiency in writing software using Python, Scala, R, or similar programming languages.
- Strong understanding and practical experience with data structures, algorithms, and software design principles.
- Ability to travel up to 30% of the time to customer sites.
Preferred Qualifications
- Experience with recommendation engines, data pipelines, or distributed machine learning.
- Familiarity with data analytics, data visualization techniques and software, and deep learning frameworks.
- Proven experience in software development, professional services, solution engineering, technical consulting, and architecting/rolling out new technology initiatives.
- Strong grasp of core data science techniques.
- Knowledge of data warehousing concepts, including technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools.
- Comprehensive knowledge of cloud computing principles, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems, and content delivery networks.
- Excellent customer-facing communication and active listening skills.
About the Google Cloud Platform Team
The Google Cloud Platform team empowers customers to innovate and build the future of their businesses using cloud technology. Our products are engineered for unparalleled security, reliability, and scalability, encompassing the entire stack from infrastructure to applications, devices, and hardware. Our dedicated teams support developers, small and large businesses, educational institutions, and government agencies in realizing the full potential of our technology. As a member of this rapidly growing, entrepreneurial team, you will play a pivotal role in understanding customer needs and influencing how businesses of all sizes leverage technology to connect with customers, employees, and partners.
Key Skills/Competency
- Machine Learning
- Artificial Intelligence
- Cloud Computing
- Data Science
- Python Programming
- Software Engineering
- Technical Consulting
- Data Pipelines
- Distributed Systems
- Customer Solutions
How to Get Hired at Google
- Research Google's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight experience in machine learning, cloud platforms, Python/Scala/R, and customer solutions relevant to a Cloud Engineer, Artificial Intelligence role.
- Prepare for technical interviews: Practice data structures, algorithms, software design, and specific ML/cloud concepts critical for Google.
- Showcase problem-solving skills: Be ready to discuss how you've designed and deployed ML solutions for complex customer challenges.
- Demonstrate Google Cloud Platform knowledge: Familiarize yourself with GCP services, especially those related to AI/ML, big data, and data warehousing.
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