Remote-First Connected Vehicle Platform Engineer

Textron Inc.; Augusta (GA); A distancia; USD 110.000 - 160.000; Jornada completa

Descripción de la vacante

Textron Specialized Vehicles in Augusta, GA is seeking a Connected Vehicle Platform Engineer to own the cloud and IoT backbone of the autonomous system, ensuring it is scalable, secure, and production-ready.

You will design reliable edge-to-cloud data architectures, build data pipelines using Kinesis, S3 and Lambda for telemetry ingestion, and deploy ML infrastructure with SageMaker, model registry, and retraining workflows.

Formación

• Bachelor’s degree in Software or Computer Engineering, IT or related field.
• 2 years of relevant experience.
• Proficiency in Python and C or similar languages.

Responsabilidades

• Own the cloud and IoT backbone of the vehicle’s autonomous system, scalable and production ready.
• Design edge-to-cloud data architectures for autonomous development and fleet operations.
• Build data pipelines for Kinesis, S3, Lambda for telemetry ingestion.
• Deploy and manage ML infrastructure: SageMaker pipelines, model registry, retraining workflows.
• Implement CI/CD and infrastructure as code (Terraform).
• Develop fleet-management tools for remote diagnostics, telemetry, and analytics.
• Establish data governance, retention and security policies for connected vehicle systems.
• Support cybersecurity controls for connected vehicle and OTA infrastructure.
• Ensure ML training and deployment pipelines operate efficiently and at scale.
• Deploy OTA updates securely to vehicles and monitor health and observability.

Conocimientos

Python

C

Real-time data

Distributed systems

Terraform

CI/CD

AWS

Educación

Bachelor's degree

Herramientas

SageMaker

Kinesis

S3

Lambda

Docker

Kubernetes/EKS

Descripción del empleo

Textron Specialized Vehicles in Augusta, GA is seeking a Connected Vehicle Platform Engineer to own the cloud and IoT backbone of the autonomous system, ensuring it is scalable, secure, and production-ready.

You will design reliable edge-to-cloud data architectures, build data pipelines using Kinesis, S3 and Lambda for telemetry ingestion, and deploy ML infrastructure with SageMaker, model registry, and retraining workflows.