Senior Principal Machine Learning Engineer

RTX

. Lead development and integration of AI/ML solutions into existing and future engineering systems .

Posted 10/22/2026full-timeEast Hartford • Connecticut • United StatesSenior💰 $132,400 - $251,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the development and integration of AI/ML solutions within engineering systems, focusing on full-stack software development, data strategy, and operational standards. Proven ability to mentor teams and drive technical adoption of AI capabilities across diverse organizational functions.

Highest-signal resume keywords

AI/ML Solution DevelopmentMLOps ImplementationCloud-Based Application DevelopmentPython Package DevelopmentTechnical Leadership in Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data StrategyFeature EngineeringModel TrainingModel DeploymentAI/ML Lifecycle ManagementAutomated TestingCode ReviewsCI/CD PracticesMachine VisionPhysics Informed Regressions

Soft Skills

MentoringCross-Functional CollaborationTechnical Enablement

Tools & Technologies

Amazon Web ServicesMicrosoft AzureTensorFlowPyTorchDatabricksMLflowAWS SageMaker StudioLLM-Based Chat Systems

Certifications & Qualifications

AWS Solution Architect AssociateAWS ML Specialty

Industry Keywords

Aerospace IndustryCompliance ProcessesEngineering Best PracticesMultidisciplinary Analysis and OptimizationExport Control

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Lead development and integration of AI/ML solutions into existing and future engineering systems
Build, test, deploy, and monitor AI systems for design optimization, product inspection, field investigation, and productivity assistants
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 integrating AI models and capabilities
Define, architect, and implement capabilities, standards, and operational processes within the P&W AI Platform Ecosystem
Lead technical adoption and enablement of enterprise AI capabilities across 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
Partner with technical and business leaders to identify, prioritize, and implement high-value AI capabilities
Build partnerships across the global Pratt & Whitney team

Requirements

What you’ll need

Bachelor's degree in Science, Technology, Engineering or Mathematics (STEM) and 10+ years of relevant digital and/or engineering experience; or Advanced Degree in a related field and 7+ years of relevant digital and/or engineering work experience
Demonstrated experience leading the development and deployment of Data & AI solutions within 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 (ChatGPT, Gemini, Copilot, etc.)
Professional Certificates for AI and Cloud Applications (e.g., AWS Solution Architect Associate or Profession, AWS ML Specialty, etc.)
Prior knowledge of the aerospace industry
Experience developing, deploying, and maintaining production cloud-based applications using 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 including 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
Engineering experience with multidisciplinary analysis and optimization (MDAO), FEA, CFD, and optimization
Disciplined software engineering experience, including automated testing, code reviews, and CI/CD
Experience navigating compliance processes for export control, legal, cybersecurity, and architectural review
U.S. citizenship is required; only U.S. citizens are authorized to access information under this program/contract

Benefits

Comp & perks

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
Annual short-term and/or long-term incentive compensation programs (eligibility-dependent and not guaranteed)