Principal Machine Learning Engineer; Hybrid

Date Posted:  Country:
United States of America

Location:

US-CT-EAST HARTFORD-ETC ~ 400 Main St ~ BLDG ETC Position Role Type:
Hybrid U.S. Citizen, U.S. Person, or Immigration Status Requirements: U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract. Security Clearance Type:
None/Not Required Security Clearance Status:
Not Required At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.

Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years. Join us and help shape the future of aerospace and defense.

Pratt & Whitney is seeking a Principal Machine Learning Engineer to join the Engineering AI Team withing the Digital Engineering Organization. The team is tasked with accelerating end-to-end AI/ML solutions across our value stream (from Engine Design and Development, Production, and Sustainment), supporting enabling AI platforms, and building our Digital Discipline. Developing and integrate AI / ML solutions into existing and future domain specific systems.

Including physics informed regressions, machine vision, language models, etc. Build, test, deploy, and monitor AI systems across multiple use cases (design optimization, product inspection, field investigation, productivity assistants, etc.) Develop and maintain AI and ML models across their lifecycle - from data gathering, feature engineering, model training, validation, deployment, and monitoring Develop and maintain full stack software systems that integrate AI models and capabilities Architect, evaluate, implement, and maintain elements of the P&W AI Platform Ecosystem (e.g., MLOps, Image Annotation, Databricks Work spaces, etc.)

Support efficient rollout of enterprise wide AI productivity tools such as Microsoft Copilot Define, document, and train AI/ML best practices

Experience product ionizing end-to-end AI systems impacting the design, make, and sustainment of Pratt & Whitney engines Experience product ionizing Data & AI driven AI applications (regression, classification, computer vision, NLP/LLM/GenAI, forecasting, anomaly detection, etc.) Experience with system administration of enabling AI tools across a large-scale user base Exposure across the Digital Tools and Data Science discipline to build proficiency across Data & AI, MDAO, Cloud Computing, etc.

Build partnerships across the global Pratt & Whitney team (Engineering, Digital, Ops and across international sites)

• Bachelor's degree in Science, Technology, Engineering or Mathematics (STEM) and 8 years of relevant digital and/or engineering experience; or Advanced Degree in a related field and 5 years of relevant digital and/or engineering work experience 3 years of relevant work experience with Data and AI or otherwise Digital-driven Engineering applications and a combination of the following: production AI/ML modeling, pipelines, system integration and model monitoring Development and deployment of software systems that integrate one or more AI components Hands on experience using LLM-based chat systems (ChatGPT, Gemini, Copilot, etc.)

• Active Secret Clearance 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 (design, analysis, manufacture, and/or aftermarket support) Experience developing, deploying, and maintaining a production cloud-based application (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 various types of AI solutions including, LLM/GenAI, Machine Vision, Physics Informed Regressions, etc.
  
  Experience with ML packages such as Tensorflow or PyTorch Experience managing AI Platforms (Databricks, mlfow server, AWS Sagemaker Studio, or other internal solutions)…