About RTX

RTX (formerly Raytheon Technologies) is a global aerospace and defense company providing advanced systems and services for commercial, military, and government customers in avionics, missiles, propulsion, and cybersecurity. Industry: Aerospace & Defense

RTX currently has 8 open roles on FindRole.

Listed pay typically runs $86,800–$165,200 across 6 roles with salary data.

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At a glance

TL;DR · Full Stack AI/ML Developer, Digital Products

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The Full Stack AI/ML Developer - Digital Products joins the Pratt & Whitney Digital Technology team to build digital products that deliver impactful user experiences. Working within cross-functional agile teams, you will design front-end architectures, develop backend services using C#, Java, and Python, and manage scalable APIs and microservices. You will collaborate with data scientists to integrate AI/ML models into applications, building inference pipelines and data workflows while managing model testing and operationalization. The role requires expertise in cloud-native platforms like Azure, AWS, or GCP, along with Databricks, Lakehouse architectures, and tools such as MLflow, PyTorch, and TensorFlow. You will also utilize Docker, Kubernetes, and Apache Kafka to support distributed systems. This position focuses on solving complex real-world problems by integrating intelligent features into modern digital solutions for the aerospace and defense sector.

Skills

AI/ML Python Java C# Spring Boot Azure AWS GCP Databricks PyTorch TensorFlow MLflow Docker Kubernetes CI/CD Apache Kafka Microservices REST APIs ETL

What you'll do

Develop front-end architectures and responsive user interfaces for digital products.
Design and implement backend services using C#, Java, and Python.
Build and maintain scalable APIs, microservices, and integration frameworks.
Integrate AI/ML models into applications including inference pipelines and intelligent features.
Build and maintain data and application pipelines to support AI/ML functionality.
Execute DevOps practices including CI/CD, automated testing, and containerized workloads.
Manage feature engineering, model testing, validation, and operationalization for stable AI usage.
Participate in Agile workflows including sprint definition and backlog prioritization.

What we're looking for

U.S. citizenship is required to access information under this program/contract.
Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field with 12+ years of experience; OR an Advanced Degree with 10+ years of experience.
10+ years of experience in data engineering, data architecture, analytics, AI/ML, or related technical domains.
5+ years of experience architecting cloud-native data platforms (Azure, AWS, or GCP).
Deep experience with Databricks, Lakehouse architectures, and modern ELT/ETL tooling.
Familiarity with AI frameworks such as MLflow, PyTorch, TensorFlow, and cloud-native ML platforms.
Strong understanding of distributed systems, real-time data streaming, data governance, and API/Integration architectures.
Security Clearance Type: None/Not.