Senior Principal ML Engineer — Hybrid Aerospace AI

RTX; East Hartford (CT); Hybrid; USD 132,000 - 252,000; Full time

Benefits offered by this job

Medical benefits

Dental & Vision

401(k) match

Paid time off

Job summary

RTX is seeking a Senior Principal Machine Learning Engineer to join the Engineering AI Team at Pratt & Whitney, focusing on AI/ML solutions across design, production and sustainment. You will lead end-to-end AI system development, including data strategy, training, deployment, and monitoring, in a hybrid work setting.

You will collaborate across Engineering, Digital, and Operations to advance enterprise AI capabilities, mentor junior staff, and drive standards for AI engineering across the

Qualifications

• Demonstrated experience leading the development and deployment of Data & AI solutions within complex engineering or enterprise environments.
• Hands on experience with LLM-based chat systems (ChatGPT, Gemini, Copilot, etc.)
• Experience leading production AI/ML solutions, including model development, deployment, MLOps, system integration, and operational support

Responsibilities

• Lead the development and integration of AI/ML solutions into existing and future engineering systems across multiple use cases.
• Define, architect, and implement AI capabilities within the P&W AI Platform Ecosystem to improve scalability and adoption.
• Lead technical adoption and enablement efforts for enterprise AI capabilities across Engineering, Digital, and Operations.
• Mentor engineers and promote engineering best practices within the organization.

Skills

LLM-based chat systems

AI/ML deployment

Data & AI solutions

Python-based packages

Education

STEM degree (Bachelor/Advanced)

Tools

Databricks

MLflow

AWS/Azure

SageMaker

Job description

RTX is seeking a Senior Principal Machine Learning Engineer to join the Engineering AI Team at Pratt & Whitney, focusing on AI/ML solutions across design, production and sustainment. You will lead end-to-end AI system development, including data strategy, training, deployment, and monitoring, in a hybrid work setting.

You will collaborate across Engineering, Digital, and Operations to advance enterprise AI capabilities, mentor junior staff, and drive standards for AI engineering across the