Hiring: Associate AI / ML Engineer (Oil, Gas & Energy Domain) Company: Capgemini Location: Houston, TX Job Posted Time: 2026-09-10 10:57:07 Employment Type: Full-time Target Skills & Keywords : AWS, Azure, CI/CD, Data Pipeline, Databricks, Docker, GCP, Git, LLM, MLOps, Machine Learning, NumPy, Pandas, PyTorch, Python, REST, RESTful, SCADA, SQL, SageMaker, TensorFlow, scikit-learn About the job Experience: •Minimum 2 to 4 years of full-time, real-time working experience developing and deploying machine learning models in live production environments. (Note: Internship experience will NOT be counted toward this requirement). •Direct hands-on experience or client project background within the Oil & Gas, Energy, Utilities, or Process Manufacturing sector. Required Skills: •Capgemini is seeking an Associate AI / ML Engineer with a solid foundation in Data Science, Machine Learning, and Software Engineering to join our Energy & Utilities practice. In this role, you will apply data-driven algorithms and AI models to solve operational challenges across upstream, midstream, or downstream oil and gas operations. •Collaborate with cross-functional technical teams and energy domain experts—including geoscientists, petroleum engineers, and software architects—to analyze complex sensor, drilling, and production datasets, build predictive models, and deploy scalable AI solutions into enterprise production workflows. •Design, build, evaluate, and fine-tune supervised, unsupervised, and predictive machine learning models tailored to energy domain workflows (e.g., predictive maintenance, yield optimization, time-series forecasting). •Extract, clean, aggregate, and engineer features from massive industrial datasets, including SCADA systems, IoT sensors, well-logs, time-series operational data, and geospatial files. •Assist in deploying, containerizing, and monitoring ML models in cloud environment pipelines (Azure, AWS, or GCP) to ensure model accuracy, stability, and latency requirements in production. •Translate complex energy sector problems (e.g., asset integrity, anomaly detection, seismic or reservoir data interpretation) into actionable machine learning solutions. •Partner with Capgemini senior data scientists, enterprise architects, and client leaders to deliver robust, production-ready digital solutions. Qualifications: •Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical/Petroleum Engineering, Physics, Applied Mathematics, or a related quantitative field. •Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) and SQL for processing large-scale operational data. •Hands-on experience working with time-series data, sensor/IoT streams, SCADA signals, or spatial/geospatial datasets commonly found in oil and gas operations. •Operational familiarity with Git version control, RESTful APIs, Docker containerization, and writing clean, maintainable, modular code. Compensation: •$46,000 - $111,000 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!