Chevron is accepting online applications for the position Machine Learning Engineer through 09 09, 2025 at 11:59 p.m. (Central Time).
Chevron is looking for a Machine Learning Engineer who can turn AI and data science ideas into real, scalable solutions. This role is about more than just building models; it’s about making them work in the real world. You’ll work closely with data scientists, software engineers, and cross-functional teams to deliver machine learning and AI systems that are reliable, efficient, and aligned with business goals.
You’ll be part of a team that’s focused on solving real problems using AI. From designing and deploying models to monitoring and maintaining them in production, your work will help drive smarter decisions and better outcomes across the company. If you’re someone who enjoys building systems that make a difference and want to work on meaningful projects with real business impact, we’d love to hear from you.
Responsibilities for this position may include but are not limited to:
Machine Learning Engineers are responsible for transforming AI and data science solutions into scalable, production-ready solutions. They bridge the gap between data science, software engineering, and IT to deliver robust machine learning systems that support business objectives.
- Solution Design & Development
- Identify data, technology, and design patterns to address business challenges using AI and ML.
- Collaborate with Data Scientists, Data Engineers, and IT teams to implement models into enterprise pipelines.
- Model Operationalization
- Transform prototypes into scalable production solutions.
- Run experiments and fine-tune algorithms for optimal performance.
- Configure infrastructure for low-latency, scalable, and resilient ML workloads.
- Deployment & Integration
- Build and maintain CI/CD pipelines for AI deployments.
- Integrate models with IT/FP MLOps infrastructure and business applications.
- Implement testing frameworks to ensure reliability.
- Monitoring & Maintenance
- Implement monitoring, alerting, and exception management for deployed models.
- Ensure inference processes generate accurate predictions and recommendations by collaborating with Data Scientists
- Bachelor’s degree in Engineering, Computer Science, or a related technical field.
- Minimum of 5 years of hands-on experience in software engineering or ML engineering with a strong focus on Python development.
- Proven experience deploying machine learning models into production environments at scale.
- Solid understanding of data science workflows and AI model lifecycle, including model training, evaluation, and inference.
- Expertise in Azure cloud services, including Azure Machine Learning and related MLOps tools.
- Demonstrated ability to troubleshoot complex systems and solve technical problems independently.
- Experience building and maintaining CI/CD pipelines for ML applications.
- Strong collaboration skills with cross-functional teams including data scientists and engineers.
- Master’s degree in Engineering, Computer Science, or Data Science.
- 7+ years of relevant technical experience.- Strong understanding of model lifecycle management and performance optimization.
Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position.
Chevron is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, sex (including pregnancy), sexual orientation, gender identity, gender expression, national origin or ancestry, age, mental or physical disability, medical condition, reproductive health decision-making, military or veteran status, political preference, marital status, citizenship, genetic information or other characteristics protected by applicable law.
We are committed to providing reasonable accommodations for qualified individuals with disabilities. If you need assistance or an accommodation, please email us at
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