Senior Video Intelligence Engineer: Multimodal AI

NRG Energy; Seattle (WA); Hybrid; USD 150,000 - 185,000; Full time

Benefits offered by this job

Medical insurance

Vision insurance

Dental insurance

401K

Flexible spending accounts

Job summary

NRG Energy is seeking a Sr Video Intelligence Engineer in Seattle to advance video understanding across video-language, summarization, and event reasoning. You will build systems that generate descriptions and insights from video and collaborate with cross‑functional teams to deploy models to production.

The role emphasizes production-quality evaluation, scalable video processing, and a mix of cloud, edge, and hybrid architectures, with a hybrid on-site schedule in Seattle.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, AI/ML, or related field with 5+ years in software/ML; or
• Master's degree in CS/AI/ML with 2+ years in software/ML

Responsibilities

• Own VLM strategy, video-language understanding, temporal video reasoning, event understanding, and multimodal embeddings.
• Improve AI Video Search, video summarization, alert relevance, recognition support, and false-alert reduction.
• Build and evaluate systems that generate natural-language descriptions, insights, and summaries from video.
• Partner with AI, platform, product, and app teams to move models from research to production.
• Develop production evaluation methods for precision, recall, grounding, latency, safety, and customer usefulness.
• Guide architecture decisions across cloud, edge, and hybrid inference paths for video intelligence.

Skills

Python

LLMs

Video processing

Git & CI/CD

Cloud & edge inference

Education

Bachelor's degree in CS/AI/ML

Master's degree in CS/AI/ML

Tools

Docker

Kubernetes

GCP/AWS

Job description

NRG Energy is seeking a Sr Video Intelligence Engineer in Seattle to advance video understanding across video-language, summarization, and event reasoning. You will build systems that generate descriptions and insights from video and collaborate with cross‑functional teams to deploy models to production.

The role emphasizes production-quality evaluation, scalable video processing, and a mix of cloud, edge, and hybrid architectures, with a hybrid on-site schedule in Seattle.