Aeromechanics Machine Learning Engineer

Job : 303169

Location
:
United Kingdom of Great Britain and Northern Ireland, Lincolnshire, Lincoln

Company
:
Siemens Energy Limited

Organization
:
Gas Services

Business Unit
:
Distributed

Full / Part time
:
Full-time

Experience Level
:
Professional / Experienced

3D ML/AI and MDO Methods Engineer (Gas Turbines) We are looking for a highly skilled Research and Development Engineer to join our team. This role focuses on developing and deploying 3D machine learning applications, surrogate models, and digital-twin-enabled workflows for the turbo machinery multi-disciplinary optimization (MDO) process chain. Develop 3D ML-based design tools and software applications for aerodynamics, heat transfer, mechanical integrity, and lifing.

Develop and validate surrogate models / digital twins according to user and project needs. Build automation scripts and workflows for MDO data preparation, model training, validation, and deployment. Integrate ML models into optimization loops and decision-support workflows. Automate engineering process steps where appropriate. The ideal candidate should have knowledge of AI / ML methods and turbo machinery engineering fundamentals.

Key responsibilities include requirements gathering, development, documentation, deployment, and maintenance of software applications. The engineer will also prepare training material and presentations to support adoption by engineering teams and improve project execution in terms of time, cost, and quality.

• Bachelor's degree in mechanical engineering, aerospace engineering, computer science, applied mathematics, or related field.
• Preference will be given to higher education like Masters or PhD.
• Strong background in developing engineering design tools, scripts, or software applications.
• Proficient programming experience (Python, C++, Java) and good Linux skills.
• Highly motivated, proactive, and self-directed.
• Excellent interpersonal and communication skills.
• Must be eligible to work on control technology as required by U.S. export control regulations.

• Strong understanding of ML model development, validation, and deployment.
• Proficiency in scientific and ML software stack (for example Num Py, pandas, scikit-learn, PyTorch or Tensor Flow).
• Working knowledge of Gitlab/Git and Linux.
• Knowledge of uncertainty quantification and model-governance best practices is a plus.

• 3+ years of experience (or relevant PhD experience) in gas or aero turbine design, MDO workflows, or ML-enabled engineering applications.

• Good understanding of gas turbine fundamentals for component design and engineering methods.
• Strong statistics, analytics, and mathematics skills.
• Knowledge of databases and data structures.
• Experience with LLMs, AI, ML, deep learning, surrogate models, or digital twins.
• Experience with high-performance computing (HPC) environments.
• Experience in Azure, AWS, or hybrid cloud environments.
• Experience developing APIs and internal engineering services.

#s1-Gen

documentation, deployment, and maintenance of software applications. The engineer will also prepare training material and presentations to support adoption by engineering teams and improve project execution in terms of time, cost, and quality.

Basic Qualifications:

Bachelor's degree in mechanical engineering, aerospace engineering, computer science, applied mathematics, or related field. Preference will be given to higher education like Masters or PhD. Strong background in developing engineering design tools, scripts, or software applications. Proficient programming experience (Python, C++, Java) and good Linux skills. Highly motivated, proactive, and self-directed. Excellent interpersonal and communication skills. Must be eligible to work on control technology as required by U.S. export control regulations.

Technical Expertise:
Strong understanding of ML model development, validation, and deployment. Proficiency in scientific and ML software stack (for example Num Py, pandas, scikit-learn, PyTorch or Tensor Flow). Working knowledge of Gitlab/Git and Linux. Knowledge of uncertainty quantification and model-governance best practices is a plus. Professional

Experience:

3+ years of experience (or relevant PhD experience) in gas or aero turbine design, MDO workflows, or ML-enabled engineering applications.

Preferred Qualifications:

Good understanding of gas turbine…