remote
Principal Engineer - AI, Machine Learning & Data Analytics - Pratt & Whitney
ML Engineer
Lead advanced AI and ML initiatives, designing scalable data analytics solutions on AWS, driving model development, deployment, and performance optimization for aerospace applications.
About the role
Key Responsibilities
- Architect and implement end‑to‑end machine learning pipelines using Python, SQL, and AWS services (S3, SageMaker, Lambda).
- Lead data engineering efforts to ingest, clean, and transform large aerospace datasets for model training and inference.
- Collaborate with cross‑functional teams to define business requirements, translate them into ML solutions, and deliver actionable insights.
- Design and maintain production‑grade model deployment workflows, ensuring scalability, reliability, and compliance with aerospace standards.
- Mentor junior engineers, conduct code reviews, and promote best practices in ML engineering and data science.
Requirements
- 10+ years of experience in AI/ML engineering with a strong background in data analytics.
- Proficiency in Python, SQL, and AWS cloud services; experience with SageMaker, Glue, and Redshift.
- Deep knowledge of machine learning algorithms, model training, hyperparameter tuning, and deployment strategies.
- Strong problem‑solving skills and ability to work independently in a remote environment.
- Excellent communication skills and a track record of delivering high‑impact solutions in complex technical domains.
Skills
pythonmachine learningawssqldeep learning