Inactive
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Baker Hughes

Makes oilfield equipment and gas turbines

Lead Industrial AI & Optimization Engineer

Applied Machine LearningPosted on Oct 5
Full-timeHouston, TX, USARemote

About the Job

Requirements

  • 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 feedforward neural networks, recurrent neural networks, including LSTMs or GRUs, convolutional neural networks, transformer models, and sequence modeling approaches.
  • Ability to work across process engineering, data science, control systems, software engineering, cloud architecture, and customer-facing product teams.
  • Strong analytical thinking, communication skills, technical documentation discipline, and ability to explain complex modeling concepts to technical and non-technical stakeholders.

Responsibilities

  • Develop 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.
  • Use industrial process engineering, advanced process control, and real-time optimization domain knowledge to develop robust machine learning algorithms.
  • Evaluate model performance, uncertainty, robustness, maintainability, and scalability in industrial deployment environments.
  • Support integration of machine learning models with optimization workflows, advanced process control systems, industrial data historians, cloud platforms, and enterprise software architectures.
  • Design, train, validate, and deploy models using Python and associated scientific, machine learning, and software development libraries.
  • Help define best practices for machine learning model lifecycle management, including data preparation, feature engineering, experiment tracking, model governance, monitoring, and continuous improvement.
  • Collaborate 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.

Desired Qualifications

  • Prior experience in energy, oil and gas, LNG, refining, petrochemicals, power generation, or industrial automation applications.

About the Company

Baker Hughes

Makes oilfield equipment and gas turbines

Baker Hughes makes equipment and runs field services for oil and gas producers, LNG plant operators, pipeline companies and industrial power users. Its products cover the whole gas chain, from drill bits and well completions to the compressors and turbines that chill natural gas into liquid for export. Its oilfield arm drills, completes and maintains wells, while its industrial arm designs, builds and services turbomachinery, valves and monitoring software. It earns money from equipment sales, project work and long-term service agreements that keep installed machines running. The current company formed in 2017 when Baker Hughes combined with GE's oil and gas business, and it is based in Houston.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1972

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