Remote Full-Stack AI/ML Engineer

globalhr; Connecticut; Remote; USD 157,000 - 299,000; Full time

Job summary

RTX is seeking a remote Full Stack AI/ML Developer for Digital Products. You will collaborate across engineering, data science, AI/ML, design, and product teams to build modern digital solutions and deliver impactful user experiences.

You will define product vision, shape roadmaps, and integrate AI/ML capabilities with scalable backend and frontend architectures. Strong cloud and data engineering background required.

Qualifications

• 10+ years in data engineering, data architecture, analytics, or AI/ML.
• 5+ years architecting cloud-native data platforms (Azure, AWS, or GCP).
• Experience with Databricks and modern ELT/ETL tooling.
• Strong knowledge of distributed systems and API/Integration architectures.
• Familiarity with ML frameworks and cloud-native ML platforms.

Responsibilities

• Collaborate with cross-functional teams to design, build, and launch digital products.
• Develop front-end architectures and intuitive interfaces.
• Design and implement backend services using C#, Java, and Python.
• Build scalable APIs, microservices, and integration frameworks.
• Integrate AI/ML models and manage data pipelines for AI features.
• Apply DevOps practices across CI/CD and cloud deployments.
• Guide product strategy, roadmaps, and stakeholder communications.

Skills

Cloud architecture

Data engineering

AI/ML integration

REST APIs

Agile methodologies

Cross-functional collaboration

DevOps practices

Education

Bachelor’s degree in Computer Science/Engineering/Data Science

Advanced degree (MS/PhD)

Tools

Databricks

Azure

AWS

GCP

PyTorch

TensorFlow

MLflow

Kubernetes

Docker

Kafka

Job description

RTX is seeking a remote Full Stack AI/ML Developer for Digital Products. You will collaborate across engineering, data science, AI/ML, design, and product teams to build modern digital solutions and deliver impactful user experiences.

You will define product vision, shape roadmaps, and integrate AI/ML capabilities with scalable backend and frontend architectures. Strong cloud and data engineering background required.