Lead Industrial AI & Optimization Engineer

location Houston, Texas, United States of America category Digital Technology Job : R169678 Posted:
Oct 5th 2026

Do you enjoy applying machine learning, advanced process control, and optimization to solve complex industrial challenges?

Would you like to help develop digital products that improve the performance, reliability, and efficiency of energy and industrial assets?

Fueling Your Passion

Join our Cordant Process Optimization Product Team!

At Baker Hughes, we develop and deploy the most advanced technologies to serve energy and industrial companies looking for more efficient, more reliable and cleaner solutions. Our diverse portfolio of technologies and solutions are transforming how industry works today and in the future.

The Cordant product portfolio brings together industrial domain expertise, software engineering, advanced analytics, and optimization technologies to help customers improve asset performance and operational decision-making across energy and industrial sectors.

Partnering with the best

We are an energy technology company that provides solutions to energy and industrial customers worldwide. Built on a century of experience and conducting business in more than 120 countries, our innovative technologies and services are taking energy forward – making it safer, cleaner, and more efficient for people and the planet.

Within the Cordant product team, you will contribute to the design, development, validation, and deployment of digital solutions that combine machine learning, process engineering, control systems, and scalable software practices. This role requires a multidisciplinary skillset spanning data-driven modeling, industrial process understanding, product-quality software development, and collaboration with cross-functional teams to deliver customer-ready capabilities.

As the Lead Industrial AI & Optimization Engineer, you will be responsible for:

• Developing machine learning and hybrid modeling solutions for industrial process applications, including neural networks, recurrent neural networks, convolutional neural networks, transformer-based architectures, and time-series models
• Utilizing industrial process engineering, advanced process control, and real-time optimization domain knowledge to develop robust machine learning algorithms
• Evaluating model performance, uncertainty, robustness, maintainability, and scalability in industrial deployment environments
• Supporting integration of machine learning models with optimization workflows, advanced process control systems, industrial data historians, cloud platforms, and enterprise software architectures
• Designing, training, validating, and deploying models using Python and associated scientific, machine learning, and software development libraries.
• Helping define best practices for machine learning model lifecycle management, including data preparation, feature engineering, experiment tracking, model governance, monitoring, and continuous improvement
• Collaboration with product managers, software engineers, process engineers, data scientists, UX teams, and customer-facing teams to deliver features aligned with product roadmaps and customer needs.

To be successful in this role you will have:

• A Bachelor’s or Master’s degree (in Chemical Engineering, Process Systems Engineering, Control Engineering, Industrial Engineering, Computer Science, Data Science, Applied Mathematics, or a related technical discipline)
• Experience developing machine learning models for engineering, industrial, time-series, or process systems applications
• Knowledge of process modeling, dynamic simulation, advanced process control, model predictive control, real-time optimization, or process optimization methods.
• Strong Python programming skills and experience with…