Lead Industrial AI & Optimization Engineer

Baker Hughes; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Flexible working

Private medical care

Education assistance

Parental leave

Life insurance and disability

Job summary

Baker Hughes is seeking a Lead Industrial AI & Optimization Engineer to drive machine learning and hybrid modeling for industrial processes across energy and industrial assets.

You will collaborate with product managers, software engineers, process engineers, data scientists, and UX teams to deliver scalable solutions and advance asset performance while working in a flexible remote US role.

Qualifications

• Bachelor’s or Master’s degree in a technical discipline is required.
• Experience developing machine learning models for engineering, industrial, time-series, or process systems applications.
• Knowledge of process modeling, dynamic simulation, and advanced process control.
• Strong Python programming skills with scientific/machine learning libraries.
• Experience with neural networks (RNNs, LSTMs, CNNs, transformers) and sequence modeling.

Responsibilities

• Develop ML and hybrid modeling solutions for industrial process applications (neural networks, RNNs, CNNs, transformers, time-series).
• Leverage process engineering and real-time optimization to build robust ML algorithms.
• Evaluate model performance, uncertainty, robustness, maintainability, and scalability in deployment.
• Support integration of ML models with optimization workflows, control systems, data historians, cloud platforms, and enterprise software.
• Design, train, validate, and deploy models using Python and related libraries.
• Define best practices for ML model lifecycle management (data, features, experiments, governance, monitoring).
• Collaborate with product managers, software engineers, process engineers, data scientists, UX teams, and customer-facing teams.

Skills

Machine learning

Advanced process control

Python programming

Data-driven modeling

Cross-functional collaboration

Education

Bachelor’s or Master’s degree in a technical discipline

Tools

Python

Cloud platforms

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 work. We invest in wellbeing, capability development, and leadership growth across all levels.

Working for you

Our innovations have transformed the energy industry for over a century. To continue progressing, we look for individuals who embrace change and contribute to building the future.

What You Can Expect

• Flexible working opportunities


• Contemporary work‑life balance policies and wellbeing activities


• Comprehensive private medical care options


• Safety net of life insurance and disability programs


• Tailored financial programs


• Education assistance


• Generous parental leave


• Mental health resources


• Dependent care support


• Additional elected or voluntary benefits

This position requires valid work authorization in the country of employment. The employer is unable to sponsor work authorization for this role at any time.

You will be eligible to participate in Company‑sponsored benefit programs, including health & welfare programs and the Thrift Plan (401k). You will have a choice of coverage options that best suit your needs. Coverage options and contribution amounts are related to your benefit elections, base salary level, and specific requirements of each of these plans.

This position is eligible for our comprehensive and competitive benefits package, which can be found here, and is further eligible for additional forms of compensation such as bonuses subject to the terms of the applicable benefit plans or policies.

The Baker Hughes internal title for this role is: Digital Technology Advisor - Product Management