Senior Ai-Native Engineer For Saas Platform (Remote Latam)
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Job summary
Google Cloud Consulting Professional Services engineers design and implement machine learning and data solutions for customer use cases, leveraging TensorFlow, DataFlow, Vertex AI and other core Google products. You will work with customers to identify opportunities, deliver workshops, and deploy solutions to production while traveling up to 30% regionally.
Be a trusted advisor, coach customers on ML systems, and collaborate with partners to deliver best practice recommendations and
Qualifications
- 8+ years of experience in data engineering or data architecture.
- Experience with Spark, Databricks, Snowflake, BigQuery, or cloud data services.
- Ability to link architecture decisions to business outcomes and explain trade-offs.
- Experience with OCI and multicloud architectures is a plus.
Responsibilities
- Discover customer's data challenges, priorities, growth expectations, and success criteria.
- Design data platforms for integration, storage, processing, and analytics.
- Design pipelines and ETL/ELT across platforms.
- Lead technical discussions, demonstrations, and proofs of concept, and help customers bring validated solutions into production.
- Help customers adopt Oracle Cloud Infrastructure (OCI) and resolve integration challenges.
- Build the data foundation for analytics, machine learning, and generative AI use cases.
Skills
Education
Tools
Job description
Senior Data and Artificial Intelligence - Cloud Solution
Partners with customers, sales, engineering and product teams to design, demonstrate and deploy Oracle Cloud architectures that address customer business problems. Drives Oracle Cloud customer consumption by accelerating the adoption of Oracle cloud services including discovery, design and deployment.
What you’ll do
What we’re looking for
If you enjoy understanding what customers need, navigating complex data environments, and helping teams put reliable solutions into production, we’d like to hear from you.
Qué harás
Qué buscamos
Si te interesa comprender las necesidades de los clientes, trabajar en entornos de datos complejos y ayudar a los equipos a llevar soluciones confiables a producción, nos gustaría conocerte.
Cloud AI Engineer, Google Cloud (English)
Share Cloud AI Engineer, Google Cloud (English)
_corporate_fare_ Google _place_ Mexico City, CDMX, Mexico; Buenos Aires, Argentina
**Early**
Experience completing work as directed, and collaborating with teammates; developing knowledge of relevant concepts and processes.
Share Cloud AI Engineer, Google Cloud (English)
_info_outline_
X
In most instances, this position requires in-person interviews as part of the hiring process.
**Please submit your resume in English - we can only consider applications submitted in this language.**
(For Mexican Applicant)
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: **Mexico City, CDMX, Mexico; Buenos Aires, Argentina** .
**Minimum qualifications:**
+ Bachelor's degree in Computer Science or equivalent practical experience.
+ Experience building machine learning solutions and working 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.
**Preferred qualifications:**
+ Experience with recommendation engines, data pipelines, distributed machine learning, and deep learning frameworks.
+ Experience in data analytics, data visualization techniques, and core Data Science methodologies.
+ Experience in software development, professional services, or technical consulting for new technology initiatives.
+ Knowledge of data warehousing (ETL/ELT), technical architectures, and big data environments (e.g., Hadoop, Spark).
+ Knowledge of cloud computing, including virtualization, multi-tenant infrastructures, and storage systems.
+ Excellent customer-facing communication and listening skills with expertise in architecting solutions.
**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'sApplicant 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 alsoGoogle'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 ourAccommodations 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.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:
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