Machine Learning Engineer, Data & Insights, Surface & HSE

Chevron Corporation

Quick summary

Work type: On-site
Location: Houston, TX
Posted: 3 days ago
Closes: Jun 16, 2026
Nearby: 51 roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $212k

$150k most similar roles pay here $260k

This listing doesn't post a salary. Most similar roles pay $173,662–$249,750.

Based on 240 similar postings.

Employer

About Chevron Corporation

Chevron Corporation is one of the world''s largest multinational energy companies engaged in the exploration, production, refining, and marketing of oil and natural gas, as well as petrochemicals and power generation. Industry: Oil & Gas Energy

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At a glance

TL;DR · Machine Learning Engineer, Data & Insights, Surface & HSE

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Chevron seeks a senior Machine Learning Engineer to join its Data & Insights team, focusing on Surface and Health Safety Environment (HSE) domains. This role involves designing and developing scalable AI solutions using Azure-based data platforms, integrating models into enterprise pipelines, and operationalizing ML systems for real-time analytics. The engineer will work closely with cross-functional teams to deploy production-ready solutions, manage CI/CD pipelines, and ensure comprehensive monitoring of deployed models. Essential skills include Python proficiency, experience with Azure cloud services, and a deep understanding of the AI lifecycle. Ideal candidates have a background in engineering or data science, 7+ years of relevant experience, and expertise in large-scale enterprise data architectures and real-time analytics platforms.

Skills

Python Azure Machine Learning CI/CD DevOps Data Governance Azure Cloud Services Kubernetes Docker Prometheus Grafana PostgreSQL Snowflake MLOps

What you'll do

Design scalable AI solutions using Azure-based data platforms for enterprise-scale analytics.
Transform ML prototypes into production-ready systems across distributed and cloud environments.
Build CI/CD pipelines for automated deployments of AI/ML models in enterprise settings.
Integrate machine learning models with MLOps infrastructure, APIs, and business applications.
Implement comprehensive monitoring systems to ensure model performance and data quality.

What we're looking for

Bachelor's degree in Engineering, Computer Science, Data Science, or related field.
7+ years experience in software engineering, ML engineering, or enterprise data platforms.
Proven track record of deploying machine learning models into production environments at scale.
Solid understanding of the AI/ML lifecycle including data preparation and model deployment.
Experience with Azure cloud services for Machine Learning and enterprise integration patterns.
Expertise in building and maintaining CI/CD pipelines for ML systems using DevOps practices.

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