Lead Industrial AI & Optimization Engineer
About The Position
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. 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.
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 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
Nice To Haves
- Prior experience in energy, oil and gas, LNG, refining, petrochemicals, power generation, or industrial automation applications; this would be an added advantage
Responsibilities
- 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.
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
- Company-sponsored benefit programs, including health & welfare programs and the Thrift Plan (401k)
- Choice of coverage options that best suit your needs
- Comprehensive and competitive benefits package
- Additional forms of compensation such as bonuses
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What This Job Offers
Job Type
Full-time
Career Level
Senior
