Senior Video Intelligence Engineer (Hybrid)

NRG; Beaverton (OR); Hybrid; USD 190,000 - 207,000; Full time

Job summary

NRG is seeking a Sr Video Intelligence Engineer to advance video understanding and multimodal AI capabilities. You will own the video-language model strategy and build systems that describe, summarize, and reason about video content for customers.

Collaboration with AI, platform, product, and app teams will move models from research to production. The role emphasizes producing accurate descriptions, scalable processing of video, and robust evaluation methods across cloud, edge, and hybrid paths.

Qualifications

• Bachelor's or Master’s in CS/AI or related field with relevant experience.
• Experience with LLMs, vision-language models, multimodal AI, or generative AI systems.
• Strong Python software engineering skills and production deployment experience.

Responsibilities

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

Skills

Python programming

Video content processing

Vision-Language

Production CI/CD

Model evaluation

Education

Bachelor's in CS/AI

Master's in CS/AI

Tools

Docker

Kubernetes

AWS

GCP

Job description

NRG is seeking a Sr Video Intelligence Engineer to advance video understanding and multimodal AI capabilities. You will own the video-language model strategy and build systems that describe, summarize, and reason about video content for customers.

Collaboration with AI, platform, product, and app teams will move models from research to production. The role emphasizes producing accurate descriptions, scalable processing of video, and robust evaluation methods across cloud, edge, and hybrid paths.