onsite
Lead Machine Learning Engineer - Chevron
ML Engineer
Lead the design, development, and deployment of production AI solutions for subsurface and wells operations, leveraging Python, advanced ML techniques, and AWS to deliver scalable, enterprise-grade systems that drive critical decision-making across upstream domains.
About the role
Key Responsibilities
- Architect and implement end‑to‑end ML pipelines that transform research‑grade models into production‑ready services on AWS.
- Collaborate with data scientists, software engineers, and domain experts to translate subsurface and wells insights into scalable AI solutions.
- Integrate ML models with enterprise data platforms, ensuring data quality, governance, and compliance across upstream operations.
- Lead model monitoring, performance tuning, and continuous improvement to maintain high reliability and accuracy.
- Mentor junior engineers and drive best practices in model versioning, CI/CD, and DevOps for ML workloads.
Requirements
- 5+ years of experience building production ML systems in a large, data‑rich environment.
- Proficiency in Python, deep learning frameworks (TensorFlow/PyTorch), and AWS services (SageMaker, Lambda, ECS).
- Strong background in data engineering, SQL, and scalable data pipelines.
- Experience with model deployment, monitoring, and lifecycle management.
- Excellent communication skills and ability to work cross‑functionally in a fast‑paced setting.
Skills
pythonmachine learningawsdeep learning