Senior Principal Machine Learning Engineer (Hybrid)
About The Position
Pratt & Whitney is seeking a Senior Principal Machine Learning Engineer for the Engineering AI Team within the Digital Engineering Organization. The team accelerates end-to-end AI/ML solutions across engine design and development, production, and sustainment; supports AI platforms; and builds the organization’s digital discipline. The role leads the development and integration of AI/ML solutions into engineering systems, including applications such as physics-informed regressions, machine vision, and language models. It oversees the lifecycle of AI/ML systems—from data strategy and feature engineering through training, validation, deployment, monitoring, and ongoing improvement—and develops full-stack software that integrates AI capabilities. The engineer also shapes capabilities, standards, and operational processes for the P&W AI Platform Ecosystem, leads enterprise adoption and enablement, and mentors engineers while promoting AI/ML engineering practices. The position is hybrid, with work regularly performed onsite and offsite. The onsite/offsite ratio is determined in partnership with the employee’s leader. U.S. citizenship is required because only U.S. citizens are authorized to access information under the program/contract. No security clearance is required.
Requirements
- Bachelor’s degree in Science, Technology, Engineering, or Mathematics (STEM) and 10 or more years of relevant digital and/or engineering experience; or an advanced degree in a related field and 7 or more years of relevant digital and/or engineering work experience.
- Demonstrated experience leading development and deployment of Data & AI solutions in complex engineering or enterprise environments, including technical leadership of significant initiatives.
- Experience leading production AI/ML solutions, including model development, deployment, MLOps, system integration, and operational support.
- Experience architecting and delivering software systems that integrate AI capabilities into engineering or business workflows.
- Hands-on experience using LLM-based chat systems such as ChatGPT, Gemini, or Copilot.
- U.S. citizenship is required to access information under the program/contract.
Nice To Haves
- Professional certificates for AI and cloud applications, such as AWS Solution Architect Associate or Professional, or AWS ML Specialty.
- Prior knowledge of the aerospace industry, including design, analysis, manufacture, and/or aftermarket support.
- Experience developing, deploying, and maintaining a production cloud-based application on Amazon Web Services or Microsoft Azure.
- Experience deploying and managing ML on edge devices.
- Experience developing, deploying, and maintaining Python-based packages or web/API applications.
- Experience implementing AI solutions such as LLM/GenAI, machine vision, and physics-informed regressions.
- Experience with ML packages such as TensorFlow or PyTorch.
- Experience defining and implementing standards, operational practices, or platform capabilities for enterprise AI environments such as Databricks, MLflow, AWS SageMaker Studio, or similar technologies.
- Experience scaling production ML and MLOps capabilities across multiple projects, products, or organizations.
- Experience leading cross-functional technical efforts involving engineering, digital, cybersecurity, legal, or compliance stakeholders.
- Demonstrated success mentoring engineers and helping establish engineering best practices within an organization.
- Engineering experience with multidisciplinary analysis and optimization (MDAO), including FEA or CFD and optimization.
- Disciplined software engineering experience, such as automated testing, code reviews, and CI/CD.
- Experience navigating export control, legal, cybersecurity, and architectural review compliance processes.
Responsibilities
- Lead development and integration of AI/ML solutions into existing and future engineering systems.
- Build, test, deploy, and monitor AI systems for use cases such as design optimization, product inspection, field investigation, and productivity assistance.
- Lead the end-to-end AI/ML lifecycle, including data strategy, feature engineering, model training, validation, deployment, monitoring, and continuous improvement.
- Develop and maintain full-stack software systems that integrate AI models and capabilities.
- Define, architect, and implement capabilities, standards, and operational processes in the P&W AI Platform Ecosystem to improve scalability, reliability, and adoption.
- Lead technical adoption and enablement of enterprise AI capabilities in partnership with Engineering, Digital, and Operations organizations.
- Establish, document, and promote AI/ML engineering standards and best practices.
- Mentor engineers and support development of the AI discipline.
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Short-term disability
- Long-term disability
- 401(k) match
- Flexible spending accounts
- Flexible work schedules
- Employee assistance program
- Employee Scholar Program
- Parental leave
- Paid time off
- Holidays
- Potential annual short-term and/or long-term incentive compensation, depending on position level and collective-bargaining coverage
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What This Job Offers
Job Type
Full-time
Career Level
Senior
