Remote Lead: Industrial AI & Optimization

Baker Hughes Company; Houston (TX); Remote; USD 130,000 - 190,000; Full time

Benefits offered by this job

Flexible working opportunities

Private medical care options

Life insurance

Disability programs

Education assistance

Generous parental leave

Mental health resources

Dependent care support

Job summary

Baker Hughes is seeking a Lead Industrial AI & Optimization Engineer to advance ML models and hybrid planning for industrial processes. This role emphasizes cross-disciplinary collaboration across process engineering, data science, software, and product teams.

Remote work in the US is possible, with a focus on delivering customer-ready capabilities and scalable solutions within the Cordant product team. Strong modeling, control theory, and Python development are essential for success.

Qualifications

• Bachelor’s or Master’s degree in Chemical Engineering, Process Systems Engineering, Control Engineering, Industrial Engineering, Computer Science, Data Science, Applied Mathematics, or 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 (feedforward, RNNs/LSTMs/GRUs, CNNs, transformers) and sequence modeling approaches.
• Ability to work across disciplines including process engineering, data science, control systems, software engineering, cloud architecture, and product teams.
• Demonstrated analytical thinking, communication skills, and ability to explain complex concepts to technical and non-technical stakeholders.
• Prior experience in energy, oil & gas, LNG, refining, petrochemicals, power generation, or industrial automation is a plus.

Responsibilities

• Develop machine learning and hybrid modeling solutions for industrial process applications.
• Utilize process engineering, advanced process control, and real-time optimization knowledge to create robust algorithms.
• Evaluate model performance, uncertainty, robustness, maintainability, and scalability in deployment environments.
• Integrate ML models with optimization workflows, control systems, data historians, cloud platforms, and enterprise software.
• Design, train, validate, and deploy models using Python and scientific libraries.
• Define best practices for ML model lifecycle management including data prep, feature engineering, experiment tracking, governance, monitoring, and improvement.
• Collaborate with product managers, software engineers, process engineers, data scientists, UX teams, and customer-facing teams.

Skills

Machine learning

Python programming

Time-series modeling

Industrial process knowledge

Strong communication

Education

Bachelor’s/Master’s degree in a related technical discipline

Tools

Cloud platforms

Industrial data historians

Job description

Baker Hughes is seeking a Lead Industrial AI & Optimization Engineer to advance ML models and hybrid planning for industrial processes. This role emphasizes cross-disciplinary collaboration across process engineering, data science, software, and product teams.

Remote work in the US is possible, with a focus on delivering customer-ready capabilities and scalable solutions within the Cordant product team. Strong modeling, control theory, and Python development are essential for success.