Cloud AI Engineer — Build ML Solutions on Google Cloud

Google LLC; Ciudad de México; On-site; MXN 900,000 - 1,300,000; Full time

Job summary

Google Cloud Consulting Professional Services in Mexico City seeks a Cloud AI Engineer to design and implement machine learning solutions for customer use cases, leveraging TensorFlow, DataFlow, and Vertex AI. You will identify opportunities to apply ML in clients' businesses and travel to customer sites to deploy solutions and run workshops.

You will collaborate with Product Management and Product Engineering to continually improve our cloud offerings and deliver production-ready ML solutions

Qualifications

• Bachelor's degree in Computer Science or equivalent practical experience.
• Experience building ML solutions and working with technical customers.
• Experience designing cloud enterprise solutions and customer projects.
• Experience with data structures, algorithms, and software design.
• Experience coding in Python.
• Ability to communicate in English fluently.

Responsibilities

• Be a trusted technical advisor to customers and solve ML challenges.
• Coach customers on ML system design, validation, monitoring, and feature management.
• Work with Customers, Partners, and Google Product teams to deploy solutions.
• Create and share best practice recommendations, tutorials, and sample code.
• Travel up to 30% in-region for meetings, technical reviews, and onsite delivery.

Skills

ML solutions

Cloud enterprise solutions

Data structures & algorithms

Python

English communication

Education

Bachelor's degree in Computer Science

Tools

TensorFlow

DataFlow

Vertex AI

Job description

Google Cloud Consulting Professional Services in Mexico City seeks a Cloud AI Engineer to design and implement machine learning solutions for customer use cases, leveraging TensorFlow, DataFlow, and Vertex AI. You will identify opportunities to apply ML in clients' businesses and travel to customer sites to deploy solutions and run workshops.

You will collaborate with Product Management and Product Engineering to continually improve our cloud offerings and deliver production-ready ML solutions