Remote Salesforce Cpq & Revenue Cloud Admin

Yo Ai Labs; Buenos Aires; Remote; ARS 181,747,000 - 272,620,000; Full time

Job summary

Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. You will design and implement machine learning solutions for customer use cases, leveraging 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.

Qualifications

• Bachelor's degree in CS or equivalent practical experience.
• 3 years experience building ML solutions and working with technical customers.
• Experience designing cloud enterprise solutions and supporting customer projects to completion.
• Experience building and deploying custom ML models into production with deep learning frameworks.
• Experience coding in Python, including data structures, algorithms, and software design.
• Ability to communicate in English fluently as this is a customer-facing role.

Responsibilities

• Be a trusted technical advisor to customers and solve complex ML challenges.
• Coach customers on feature extraction, data validation, monitoring, and feature/model management.
• Collaborate with Customers, Partners, and Google Product teams to deliver production-ready solutions.
• Create and deliver best practice tutorials, blog articles, and sample code.
• Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities.

Skills

Python

Machine Learning

Cloud architecture

English fluency

Mentoring

Education

BSc in CS

Tools

TensorFlow

PyTorch

XGBoost

Apache Hadoop

Apache Spark

Job description

Salesforce Commerce Cloud Developer

Cloud AI Engineer IV, Google Cloud (English)

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Minimum qualifications:

• Bachelor's degree in Computer Science or equivalent practical experience.
• 3 years of experience building machine learning solutions and working with technical customers.
• Experience designing cloud enterprise solutions and supporting customer projects to completion.
• Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
• Experience coding in Python, including data structures, algorithms, and software design.
• Ability to communicate in English fluently as this is a customer-facing role.

Preferred qualifications:

• Experience working with recommendation engines, data pipelines, or distributed machine learning.
• 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 the 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 closely with Product Management and Product Engineering to build and constantly drive excellence in our products.

In this role, you will work with key Google Cloud customers. Together with the team, you will support customer implementation of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.

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 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.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.