Chevron is seeking a forward-thinking Lead Machine Learning Engineer to evaluate and integrate emerging and start-up Artificial Intelligence (AI) and Machine Learning (ML) solutions that drive value for Chevron.
Requirements
- Significant experience engineering solutions in Python with strong understanding of control flow, functions, data structures and object-oriented programming concepts.
- Experience implementing machine learning frameworks and libraries (e.g. ML Flow, Kubeflow, Tensorflow. Keras scikit-learn, PyTorch, NumPy, SciPy, etc.).
- Development experience with a JavaScript framework (Angular, React, node.js etc.).
- Experience building machine learning pipelines in Microsoft Azure Machine Learning service.
- Experience developing cloud first solutions using Microsoft Azure Services (Azure Functions, Azure App Services, Azure Event hubs, Azure SQL DB, Azure Synapse etc.).
- Working knowledge of mathematics (primarily linear algebra, probability, statistics), and algorithms.
- Knowledge of data engineering and transformation tools and patterns such as DataBricks, Spark, Azure Data Factory.
Responsibilities
- Partner with Digital Innovation Teams to evaluate and test emerging AI and Machine Learning technologies.
- Explore and experiment with applications of Generative AI (GenAI), NLP, and computer vision.
- Stay current with the latest advancements in AI and integrate them into projects.
- Build and maintain robust data pipelines using platforms like Databricks.
- Deploy models in production using Docker and cloud platforms (e.g., AWS, Azure).
- Conduct ML tests and experiments to validate hypotheses and improve performance.
- Transform data science prototypes into appropriate scale solutions in a production environment.
Other
- BS in Computer Science, Mathematics, or related fields or equivalent experience.
- 5+ years’ experience in Software Engineering.
- 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.
- Relocation is not offered for this role. Only local candidates will be considered.
