[Hiring] Lead Industrial AI & Optimization Engineer @Baker Hughes

Role Description

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.

Qualifications

• 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.

Requirements

• 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.

Benefits

• 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.