Chevron is accepting online applications for the position Lead Machine Learning Engineer through May 15th, 2025 at 11:59 p.m. (CST)
Overview
Chevron is seeking a Machine Learning Engineer to transform AI and data science concepts into scalable, production-grade solutions. You will build, deploy, and maintain machine learning systems that operate reliably at enterprise scale. Working alongside data scientists, software engineers, and cross-functional partners, you will bridge the gap between research and production to deliver AI systems aligned with strategic business objectives. Your work will drive smarter decisions and measurable outcomes across the organization.
Responsibilities for this position may include but are not limited to:
Solution Design & Development
- Identify data sources, technology stacks, and design patterns to address business challenges using AI and ML.
- Partner with Data Scientists, Data Engineers, and IT teams to integrate models into enterprise data pipelines and workflows.
Model Operationalization
- Transform prototypes into scalable, production-ready solutions.
- Design and execute experiments to fine-tune algorithms for optimal performance, latency, and resource efficiency.
- Configure and manage infrastructure for low-latency, highly available, and resilient ML workloads.
Deployment & Integration
- Build, maintain, and optimize CI/CD pipelines for automated AI/ML deployments.
- Integrate models with enterprise MLOps infrastructure and downstream business applications.
- Develop and implement testing and validation frameworks to ensure model reliability and reproducibility.
Monitoring & Maintenance
- Implement comprehensive monitoring, alerting, and exception-handling systems for deployed models.
- Collaborate with Data Scientists to ensure inference processes produce accurate, consistent predictions and recommendations.
- Proactively identify and resolve model drift, performance degradation, and system issues.
Required Qualifications
- Bachelor's degree in Engineering, Computer Science, or a related technical field.
- Minimum 7 years of hands-on experience in software engineering or ML engineering, with strong proficiency in Python.
- Proven track record of deploying machine learning models into production environments at scale.
- Experience with agentic AI frameworks and workflows (e.g., multi-step reasoning, tool use, orchestration patterns such as LangGraph, Semantic Kernel, or MSFT Agent Framework).
- Solid understanding of the AI model lifecycle, including data preparation, model training, evaluation, deployment, and inference.
- Expertise in Azure cloud services, including Azure Machine Learning and associated MLOps tooling.
- Experience building and maintaining CI/CD pipelines for ML applications.
- Demonstrated ability to troubleshoot complex distributed systems and resolve technical issues independently.
- Strong collaboration and communication skills, with experience working across data science, engineering, and business teams.
Preferred Qualifications
- Master's degree in Engineering, Computer Science, Data Science, or a related field.
- 10+ years of relevant technical experience.
- Deep understanding of model lifecycle management, performance optimization, and ML system design patterns.
Relocation Options:
Relocation is not offered for this role. Only local candidates will 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.
Houston, Texas
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