Chevron's Business Support Center (BASSC), located in Buenos Aires, is accepting applications for the position of Data Engineer - ML teams. Successful candidates will join the IT Organization, which is part of a multifunction service and technical center with a workforce of more than 1800 employees that deliver business services and solutions to the corporation across the globe.

Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design. A Data Engineer designs data products and data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective.

Required Qualifications

• Minimum 5 years' experience in Object Oriented Design and Programming and Python development.
• Experience implementing machine learning frameworks and libraries
• Development experience with a JavaScript framework, experience building machine learning pipelines in Microsoft Azure Machine Learning service
• Experience developing cloud first solutions using Microsoft Azure Services
• Experience building multi-agent LLM solutions using Microsoft Azure AI, Databricks, or comparable ecosystems, including tool/function calling, orchestration, guardrails, evaluators, and related capabilities.
• Strong NLP expertise, including text processing, embedding generation, semantic search, and retrieval optimization.
• Proficiency with Retrieval-Augmented Generation (RAG) patterns, vector indexing, grounding strategies, and metadata-driven retrieval.

Preferred Qualifications

• Experience with Microsoft Copilot Studio, including agent creation, orchestration, publishing, and extension through custom skills
• Power Platform integration expertise, including custom connectors and end-to-end solution deployment
• Strong Databricks experience, including Unity Catalog, Delta Lake, feature engineering, and data pipelines
• Data engineering and data modeling proficiency, with deep understanding of ETL/ELT workflows and scalable data architectures
• Familiarity with Responsible AI, security, and privacy best practices in enterprise AI systems
• Proficient in applying common design patterns, ability to communicate design ideas effectively.
• Must have a disciplined, methodical, minimalist approach to designing and constructing layered software components that can be embedded within larger frameworks or applications.
• Hands-on experience in deploying machine learning pipelines with Azure Machine Learning SDK. Knowledge of enterprise SaaS complexities including security/access control, scalability, high availability, concurrency, online diagnoses, deployment, upgrade/migration, internationalization, and production support.
• Knowledge of data engineering and transformation tools and patterns such as DataBricks, Spark, Azure Data Factory.
• Mature software engineering skills, such as source control versioning, requirement spec, architecture and design review, testing methodologies, CI/CD, etc.
• Ability to engage business and technical experts at all organizational levels and assess opportunities to apply machine learning and analytics to improve their workflows and deliver information and insight to support business decisions.
• Proven ability to take leadership role in projects that span multiple teams and ability to work with product managers to clarify and prune requirements.
• Ability to build collaborative relationships across functional and geographic areas to plan, facilitate, and architect and develop scalable AI solutions for Chevron's key business units and functions.
• Ability to communicate in a clear, concise, and understandable manner both orally and in writing.

Relocation Options:

Relocation could be considered.

International Considerations:

Expatriate assignments will not be considered.

Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position

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