AI/ML Systems Engineer

POSITION SUMMARY: This position extends traditional aerodynamic product development by creating and integrating custom AI/ML applications, pipelines, and data systems into turbomachinery workflows. The engineer supports aero stage development, improves predictive capability using data-driven methods, and develops scalable tools to enhance engineering efficiency, bridging aero performance engineering with modern software and data engineering.
The role also includes aggregation and structuring of legacy TAG data to generate insights on global Category 1 & 2 part reliability, as well as aggregation and restructuring of legacy sales and operational datasets to enable machine learning model development and training.

KEY ACCOUNTABILITIES:

• Design, train, and deploy custom AI/ML models (e.g., neural networks, CNNs, surrogate models) to enhance compressor/turbine performance prediction and accelerate simulation workflows.
• Support aerodynamic stage development through data-driven analysis, performance correlation, optimization, and physics-informed / hybrid ML methods.
• Build and maintain structured data systems for geometry, CFD, test, and engine datasets using scalable ETL pipelines, SQL, and cloud-based data architectures.
• Integrate AI/ML models into engineering workflows including CFD, FEA, test analysis, and product development toolchains.
• Develop and own end-to-end ML pipelines (Python, APIs, dashboards), including feature engineering, model training, hyperparameter tuning, validation, and deployment.
• Collaborate with aero engineers to augment classical turbomachinery and applied physics methods with data-driven and statistical learning approaches.
• Execute rigorous model validation against test stand and engine data, including uncertainty quantification, robustness assessment, and performance generalization.
• Develop reusable ML frameworks and guide technical execution, documentation, and adoption of AI/ML methods across Product Development initiatives.

QUALIFICATIONS:

• Bachelor of Science in Computer Science, Statistics, Engineering, or related discipline with strong foundation in applied mathematics and statistics.
• Strong programming skills in Python; experience with additional languages (JavaScript, C/C++) and software engineering practices is a plus.
• Hands-on experience developing, training, and optimizing ML models (PyTorch, TensorFlow), including neural networks (NNs, CNNs) and data-driven modeling approaches.
• Experience with SQL and database systems; familiarity with ETL pipelines, Azure Data Factory, or similar distributed data platforms.
• Solid understanding of algorithms, numerical optimization, probability theory, applied statistics, and data structures.
• Demonstrated experience developing production-quality data-driven applications, ML models, or analytical tools.
• Exposure to aerodynamics, turbomachinery, CFD, or physics-based engineering systems preferred.
• Strong analytical and problem-solving capability with ability to translate complex engineering problems into scalable ML/statistical solutions.

𝗦𝗸𝗶𝗹𝗹𝘀:

 

Effectively Present Solutions, Planning and Organizing, Policies & Procedures, Relationship Maintenance, Strategic Questioning

Salary Range:

$77,600 - $109,125

Internal Use Only: Salary

Global Terms of Use and Privacy Statement

Carefully read the BorgWarner Privacy Policy before using this website. Your  ability to access and use this website and apply for a job at BorgWarner are conditioned on your acceptance and compliance with these terms.

Please access the linked document by clicking here, select the geographical area where you are applying for employment, and review. Before submitting your application you will be asked to confirm your agreement with the terms.

Career Scam Disclaimer:  BorgWarner makes no representations or guarantees regarding employment opportunities listed on any third-party website.  To protect against career scams, job applicants should take the necessary precautions when interviewing for and accepting employment positions allegedly offered by BorgWarner.  Applicants should never provide their national ID numbers, birth dates, credit card numbers, bank account information or other private information when communicating with prospective employers or responding to employment opportunities online.  Job applicants are invited to contact BorgWarner through BorgWarner’s website to verify the authenticity of any employment opportunities.