Lead Industrial AI & Optimization Engineer

Baker Hughes; Houston (TX); Remote; USD 150,000 - 230,000; Full time

Job summary

Baker Hughes is seeking a Lead Industrial AI & Optimization Engineer to advance machine learning, process control, and optimization for industrial assets. You will join the Cordant Process Optimization Product Team and help design, validate, and deploy digital solutions that enhance performance and reliability across energy and industrial sectors.

The role requires a multidisciplinary skillset spanning data-driven modeling, process understanding, and scalable software practices, with remote

Qualifications

• Experience building ML models for engineering/industrial processes.
• Knowledge of process modeling, dynamic simulation, and real-time optimization.
• Strong Python programming and ML library experience.
• Ability to work across process engineering, data science, control systems, and software teams.

Responsibilities

• Develop ML and hybrid modeling solutions for industrial processes.
• Leverage process engineering, advanced process control, and real-time optimization knowledge.
• Evaluate model performance, uncertainty, robustness, and scalability in deployment.
• Integrate ML models with optimization workflows, control systems, data historians, and cloud platforms.
• Design, train, validate, and deploy models using Python and ML libraries.
• Define best practices for model lifecycle management, governance, and monitoring.
• Collaborate with product, software, and customer-facing teams to align with roadmaps.

Skills

Machine learning

Advanced process control

Optimization

Python

Cross-disciplinary collaboration

Education

Bachelor's or Master's degree in Chemical Engineering or related technical discipline

Tools

Python

Job description

Lead Industrial AI & Optimization Engineer

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
• Collaborating 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 common scientific and machine learning libraries
• Practical experience with neural network architectures, including feedforward neural networks, RNNs, LSTMs or GRUs, CNNs, transformer models, and sequence modeling approaches
• Ability to comfortably work across disciplines, including process engineering, data science, control systems, software engineering, cloud architecture, and customer-facing product teams
• Demonstrated strong analytical thinking, communication skills, technical documentation discipline, and ability to explain complex modeling concepts to technical and non-technical stakeholders
• Prior experience in energy, oil and gas, LNG, refining, petrochemicals, power generation, or industrial automation applications; this would be an added advantage

Work in a Way That Works for You

We recognize that everyone is different and that the way people want to work and deliver at their best is different for everyone too. In this role, flexible working patterns may be available depending on business needs, role requirements, and local policies. The role is open to remote working in the US.

Working with us

Our people are at the heart of what we do at Baker Hughes. We know we are stronger when our people are developed, engaged, and empowered to bring their authentic selves to