Senior AI Engineer - Edge & Cloud Vision

NRG Energy; Lehi (UT); On-site; USD 110,000 - 160,000; Full time

Job summary

NRG Energy is seeking an AI Engineer for its Camera AI team to build practical computer vision solutions that enhance home protection and user convenience. You will work across edge and cloud platforms, shaping data workflows from collection to training, and collaborating with embedded, apps, and UX teams to deploy robust AI features.

The role focuses on scalable ML development, model evaluation, and ongoing performance monitoring in production, supporting a growing smart home ecosystem with

Qualifications

• Bachelor's/Master's/PhD in data science, CS, CE or related field with 3-5 years of relevant experience.
• Strong analytical and problem-solving skills applied to AI/ML.
• Experience in computer vision, data curation, and model pipelines.

Responsibilities

• Lead design and development of scalable AI features with customer impact.
• Collaborate with embedded, apps, platform, QA, product, and UX teams to deploy AI at scale.
• Create, test, and refine ML models for edge and cloud environments.
• Develop data management pipelines including curation, annotation, and training.
• Monitor production AI features and drive iterative improvements.

Skills

AI/ML Experience

Computer Vision

Data Structures & Pipelines

Rust

C++

Python

Shell

Embedded Linux

Git

Education

Bachelor's degree in data science, computer science, electrical/computer engineering or related field

Tools

TensorFlow

PyTorch

FiftyOne

CVAT

Vertex AI

Label Studio

DVC

CML

Gitlab Pipelines

GStreamer

ffmpeg

mediapipe

Job description

NRG Energy is seeking an AI Engineer for its Camera AI team to build practical computer vision solutions that enhance home protection and user convenience. You will work across edge and cloud platforms, shaping data workflows from collection to training, and collaborating with embedded, apps, and UX teams to deploy robust AI features.

The role focuses on scalable ML development, model evaluation, and ongoing performance monitoring in production, supporting a growing smart home ecosystem with