Machine Learning & Artificial Intelligence Engineer

Job Description Summary
Become part of a winning team and help to deliver the Green Energy transition.

This position will be responsible for developing ML & AI methodologies.

Main focus of the role:
oAPOW (Automated Process and Optimisation Workbench) - tool reconstruction, develop this tool and develop new ideas.

oProgramming

oMachine Learning & AI

oMentoring and supervising a team of 4

GE Vernova is a multi-national organisation, employing over 80,000 people worldwide.

In the GE Vernova Gas Power Analytics & Digital engineering team, based in Rugby, we are constantly evaluating methods and algorithms that offer the opportunity to improve the efficiency and effectiveness of our engineering design and analysis tools and processes. Our main area of interest is automation and optimisation of engineering design processes.

• We require for a computer science engineer. This role will include the study of ML-AI techniques for our engineering applications. The scope of work is expected to be, but not limited to
• AI Engineer and Machine Learning focus
• APOW (Automated Process and Optimisation Workbench) - tool reconstruction, develop this tool and develop new ideas.
• Mentoring and supervising a team of 4
• Design, develop, test, and deploy clean, modular, and well-documented pipelines to build machine learning components, integrating them into the in-house platform to support the adoption of AI tools by engineers.
• Maintain and enhance existing machine learning capabilities, including data management, computer vision and regression tools.
• Translate stakeholder challenges and requirements into actionable, effective solutions.
• Stay up to date with the latest advancements in AI techniques and tools to ensure the application of state-of-the-art solutions.

• Post-graduate degree in Computer Science, Statistics, Machine Learning or Data Science.

• Solid foundation of Digital and Web methodology implementation.
• Understanding of MLOps principles and practices.
• Significant Java programming skills, including Swing and Java-FX.
• Experience in Linux & Windows operating systems.
• Good communication skills.
• Good, adaptable team worker, eager to learn and develop.
• Ability and confidence to work independently.
• This role involves work for customers who manage critical infrastructure; based on customer requirements it will be necessary to carry out background checks and suitability assessments (e.g. UK Security Clearance (SC)) as part of the hiring process.

• Workflow Automation: Standardise routine calculation and simulation tasks (such as Computational Fluid Dynamics or CFD) to capture institutional knowledge.

• Mathematical Integration: Connects established workflows with math routines to evaluate system performance.

• Design Exploration: Runs Design of Experiments (DoE) to test how adjustments in shape or parameters affect overall output.

• Optimisation & Machine Learning: Integrates optimisation algorithms and surrogate modeling (like Kriging models) to accelerate design enhancements and uncertainty quantification (UQ).

• Used heavily in turbomachinery and power generation design.

• Optimises physical components like turbine endwalls, casings, and stators to improve aerodynamic efficiency and reduce emissions.