Data Engineer
hace 5 días
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 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.-
- 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
Chevron participates in E-Verify in certain locations as required by law.
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