Senior Industrial AI & Optimization Engineer (Remote)

Baker Hughes Holdings LLC; Houston (TX); Remote; USD 140,000 - 190,000; Full time

Job summary

Baker Hughes is seeking a Lead Industrial AI & Optimization Engineer to develop ML and hybrid models for industrial applications. You will leverage process engineering, advanced control, and optimization to deliver scalable solutions, collaborating with cross-functional teams to align with product roadmaps.

The role supports deployment across energy and industrial assets, with emphasis on robustness, experimentation, and governance, and offers remote work options within the US.

Qualifications

• Bachelor's or Master's in Chemical/Process/Control Engineering, CS, or related field.
• Experience developing ML models for engineering, industrial, time-series, or process systems.
• Knowledge of process modeling, dynamic simulation, and real-time optimization.
• Strong Python programming skills with scientific libraries.
• Experience with neural networks (FFN, RNNs, LSTMs/GRUs, CNNs, transformers).
• Ability to work across process engineering, data science, software, and product teams.

Responsibilities

• Develop machine learning and hybrid models for industrial processes.
• Utilize process engineering and advanced control knowledge to craft robust ML algorithms.
• Evaluate model performance, robustness, and scalability in deployment.
• Integrate ML models with optimization workflows and control systems.
• Design, train, validate, and deploy models using Python and ML libraries.
• Define lifecycle governance, data prep, experiment tracking, and monitoring.
• Collaborate with product managers, engineers, data scientists, and UX teams.

Skills

ML & optimization

Python programming

Cross-disciplinary collaboration

Analytical thinking

Communication skills

Education

Bachelor's or Master's in Engineering/CS/Math

Tools

Python

Cloud platforms

Enterprise software architectures

Job description

Baker Hughes is seeking a Lead Industrial AI & Optimization Engineer to develop ML and hybrid models for industrial applications. You will leverage process engineering, advanced control, and optimization to deliver scalable solutions, collaborating with cross-functional teams to align with product roadmaps.

The role supports deployment across energy and industrial assets, with emphasis on robustness, experimentation, and governance, and offers remote work options within the US.