Cloud AI Engineer — Enterprise ML Solutions (Travel 30%)

Coodesh, Inc.; Ciudad de México; On-site; MXN 600,000 - 1,200,000; Full time

Job summary

Google Cloud Consulting Professional Services helps customers transform their business using Google Cloud, TensorFlow, DataFlow, and Vertex AI. As a Cloud AI Engineer, you will design and implement ML solutions for customer use cases and travel to customer sites to deploy them.

You will work with Product teams to improve products, educate customers through workshops, and guide architecture, data migration, and capacity planning across engagements. This is a global role with in-region travel.

Qualifications

• Bachelor's degree in Computer Science or equivalent.
• Experience building machine learning solutions and with technical customers.
• Experience designing cloud enterprise solutions and supporting customer projects to completion.
• Experience with data structures, algorithms, and software design.
• Experience coding in Python.
• Ability to communicate in English fluently to collaborate with other teams.

Responsibilities

• Be a trusted technical advisor to customers and solve complex machine learning challenges.
• Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
• Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
• Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
• Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities.

Skills

ML solutions experience

Cloud enterprise solutions

Data structures & algorithms

Python programming

English communication

Education

Bachelor's degree in Computer Science

Job description

Google Cloud Consulting Professional Services helps customers transform their business using Google Cloud, TensorFlow, DataFlow, and Vertex AI. As a Cloud AI Engineer, you will design and implement ML solutions for customer use cases and travel to customer sites to deploy them.

You will work with Product teams to improve products, educate customers through workshops, and guide architecture, data migration, and capacity planning across engagements. This is a global role with in-region travel.