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Cloud Engineer, AI, Google Cloud (English, Spanish)

AT Google
Google

Cloud Engineer, AI, Google Cloud (English, Spanish)

Mexico City, Mexico

Minimum qualifications:

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 4 years of experience building machine learning solutions and working with technical customers.
  • Experience coding in one or more general purpose languages (e.g.,Python, Java, Go, C or C++) including data structures, algorithms, and software design.
  • Experience designing cloud enterprise solutions and supporting customer projects to completion.
  • Ability to communicate in English and Spanish fluently to engage with local stakeholders.
Preferred qualifications:
  • Experience working with recommendation engines, data pipelines, or distributed machine learning.

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  • Experience with deep learning frameworks (e.g. Tensorflow, pyTorch, XGBoost).
  • Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g.,Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
  • Understanding of auxiliary practical concerns in production machine learning systems.

  • About the job

    The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google's global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

    As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work with Product Management and Product Engineering to build and constantly drive excellence in our products.

    In this role, you will be working with aspiring Cloud customers. You will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, etc.

    Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

    Responsibilities

    • Be a trusted technical advisor to customers and solve complex machine learning issues.
    • Coach customers on the practical test 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% of time in-region for meetings, technical reviews, and onsite delivery activities as needed.

    Client-provided location(s): Mexico City, CDMX, Mexico
    Job ID: Google-126980227543769798
    Employment Type: Other

    Perks and Benefits

    • Health and Wellness

      • Health Insurance
      • Dental Insurance
      • Vision Insurance
      • Life Insurance
      • Short-Term Disability
      • Long-Term Disability
      • FSA
      • HSA
      • Fitness Subsidies
      • On-Site Gym
      • Mental Health Benefits
      • Health Reimbursement Account
      • HSA With Employer Contribution
    • Parental Benefits

      • Birth Parent or Maternity Leave
      • Non-Birth Parent or Paternity Leave
      • Fertility Benefits
      • Adoption Assistance Program
      • Family Support Resources
      • Adoption Leave
    • Work Flexibility

      • Hybrid Work Opportunities
    • Office Life and Perks

      • Commuter Benefits Program
      • Casual Dress
      • Pet-friendly Office
      • Snacks
      • Some Meals Provided
      • On-Site Cafeteria
    • Vacation and Time Off

      • Paid Vacation
      • Paid Holidays
      • Personal/Sick Days
      • Leave of Absence
      • Volunteer Time Off
    • Financial and Retirement

      • 401(K) With Company Matching
      • Company Equity
      • Performance Bonus
      • Financial Counseling
    • Professional Development

      • Tuition Reimbursement
      • Internship Program
      • Learning and Development Stipend
    • Diversity and Inclusion

      • Employee Resource Groups (ERG)

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