AI & ML Engineer

Artificial Intelligence and Machine Learning Engineer

Location: Oklahoma City, OK

Reports to: VP, Data Science

Employment Type: Salary, Exempt Full-Time

About Us

Western Natural Resources (WNR) is a privately held, Oklahoma City–based oil and gas company focused on acquiring, developing, and operating high-quality upstream energy assets. Founded through a strategic partnership between Centalion and experienced energy leaders, WNR combines deep industry expertise, disciplined execution, and a long-term approach to building a premier energy company.

WNR is a rapidly growing organization with an entrepreneurial culture where collaboration, integrity, safety, and accountability are central to how we operate. As the company expands its asset base and team, employees have the opportunity to make a meaningful impact, work closely with experienced industry leaders, and help build the infrastructure and culture of a growing energy company.

Position Summary

Western Natural Resources is hiring an AI/ML Engineer to build the machine learning models and analytics applications that help the company make better technical and commercial decisions — turning the data on our Databricks lakehouse into tools that engineers, operations, accounting, land, and leadership use every day.

This is a hands-on role on a small team. You will work side by side with employees across the organization to understand the problems they are trying to solve, build and validate the models behind the answers in Databricks, and ship them as applications people actually use. We build with agentic AI coding tools as a normal part of the workflow and expect the same here — used with judgment, with results verified against the data.

Key Responsibilities

• Work directly with engineers and business stakeholders across reservoir engineering, operations, accounting, and land to understand the problems they face and turn them into well-scoped analytics solutions.
• Build, train, validate, and deploy machine learning models in Databricks - forecasting, predictive, and optimization models that support operating and capital decisions, using MLflow to track experiments and manage model versions.
• Build applications and dashboards that put model outputs in front of users across the company - tools people use to make decisions, not one-off analyses.
• Develop with agentic AI coding tools (Claude Code or similar) to prototype and ship quickly, verifying results against the data and against the judgment of the people who will use them.
• Validate models rigorously: backtest, quantify uncertainty, and explain in plain terms where a model can and cannot be trusted.
• Deploy and monitor models and applications in production - including retraining and catching drift or degraded results before a user does.
• Partner with the data engineering team to build on the lakehouse's curated tables, and bring data needs back to the platform.
• Work alongside users through iteration: gather feedback, refine the tools, and document and train so adoption sticks.

Required Qualifications

• Bachelor's degree in Engineering, Computer Science, Statistics, Data Science, or a related field.
• Upstream oil and gas experience in working knowledge of the problems engineers and business stakeholders solve, such as production and reserves forecasting, well performance, and economics
• \+ years building and deploying machine learning models, from data preparation and feature engineering through training, validation, and deployment
• Strong hands-on Python and SQL. This role writes code daily.
• Solid foundation in statistics and machine learning: model selection, validation, and diagnosing when a model is wrong
• Experience building applications, dashboards, or APIs that put model results in front of end users
• Working fluency with agentic AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar), and the judgment to know when their output has to be verified
• Git-based version control and code review as a normal part of your workflow
• Ability to work directly with non-technical stakeholders, translate business problems into analytical solutions, and communicate clearly in writing and in person
• Ability to work independently in a small-team environment

Preferred Qualifications

• Master's degree in Data Science, Analytics, or a related technical field
• Databricks experience, including MLflow, Delta Lake, Unity Catalog, and job orchestration, and production experience with Spark (PySpark and Spark SQL)
• Building LLM-powered or agentic applications in production
• BI tools such as Spotfire or Power BI

What We Offer

• Competitive base salary \+ performance-based incentives
• Direct influence on how WNR makes decisions, with tools you build used across the company
• A modern cloud data and AI stack, with real input into the tools and architecture
• Flat, collaborative team structure with fast decision-making

Physical Requirements

Ability to perform the essential functions of the position, including sitting, standing, walking, communicating, and using standard office or job-related equipment. May require lifting, travel, working outdoors, or use of personal protective equipment.