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Data Engineer - ML

Buenos Aires, Argentina

R000068145

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  • Full-Time
  • Level: 8+ years of experience
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Demonstrate core high performance behaviors – thrive in a highly collaborative, project-based environment, and tackle complex business problems to reach creative, yet practical solutions.

  • Collaborative
  • Analytical
  • Communicator
  • Strategic
  • Results-Driven
  • Problem-Solver

Data Engineer - ML

Buenos Aires, Argentina

R000068145

apply now

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 

Preferred Qualifications

  • Working knowledge of mathematics (primarily linear algebra, probability, statistics), and algorithms.

  • 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.

  • Proficient at orchestrating large-scale ML/DL jobs, leveraging big data tooling and modern container orchestration infrastructure, to tackle distributed training and massive parallel model executions on cloud infrastructure.

  • Experience designing custom APIs for machine learning models for training and inference processes and designing, implementing, and delivering frameworks for MLOps.

  • Experience implementing and incorporating ML models on unstructured data using cognitive services and/or computer vision as part of AI solutions and workflows.

  • History of working with large scale model optimization and hyperparameter tuning, applied to ML/DL models.

  • 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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