Remote Lead Gen Specialist - Entry Level | Ai Outreach

Virtustant; Quilmes; A distancia; ARS 139.086.000 - 231.811.000; Jornada completa

Descripción de la vacante

Google Cloud Careers seeks an AI Analyst – Agentic AI, Backend & Data Developer. The role focuses on designing and implementing machine learning solutions for customer use cases, leveraging TensorFlow, DataFlow, and Vertex AI.

You will work with customers to identify opportunities to apply ML in their business, and travel to customer sites to deploy solutions and deliver workshops. You will collaborate with Product Management and Product Engineering to continually enhance Google Cloud products

Formación

• 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 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.

Responsabilidades

• Be a trusted technical advisor to customers and solve complex machine learning challenges.
• Coach customers on practical challenges in ML systems: feature extraction, validation, monitoring, and 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.

Conocimientos

Bachelor level CS

ML model deployment

Python programming

English communication

Cloud enterprise solutions

Agentic AI workflows

Educación

Bachelor's degree in Computer Science

Herramientas

TensorFlow

PyTorch

XGBoost

Apache Beam

Hadoop

Spark

Pig

Hive

MapReduce

Flume

Descripción del empleo

AI Analyst - Agentic AI, Backend & Data Developer

Cloud AI Engineer, Google Cloud (English)
Share Cloud AI Engineer, Google Cloud (English)
_corporate_fare_ Google _place_ Buenos Aires, Argentina; Mexico City, CDMX, Mexico
**Mid**
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.
Share Cloud AI Engineer, Google Cloud (English)
_info_outline_
XIn most instances, this position requires in-person interviews as part of the hiring process.
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Buenos Aires, Argentina; Mexico City, CDMX, Mexico** .
**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.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy (./privacy-policy).
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. See also Google's EEO Policy ( ,Know your rights: workplace discrimination is illegal ( ,Belonging at Google ( , andHow we hire ( .
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form ( .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.