Sr Software Engineer, Video Intelligence

Vivint pioneers smart home security solutions by combining intelligent hardware, real-time sensor data, and AI to help customers live safer, smarter, and more sustainable lives. The Senior Video Intelligence Engineer will advance video understanding through video-language, summarization, context, and event-reasoning capabilities, while partnering across teams to deploy reliable camera intelligence systems into production.

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 useful 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

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 5+ years of professional experience in software development, applied science, or ML engineering; or
• Master's degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 2+ years of professional experience in software development, applied science, or ML engineering
• Experience with LLMs, vision-language models, multimodal AI, or generative AI systems
• Strong Python software engineering skills
• Experience processing, analyzing, or serving video content at scale
• Familiarity with event detection, summarization, semantic understanding, embeddings, or model evaluation
• Experience deploying AI services into production with Git and CI/CD workflows
• Experience generating natural-language descriptions, summaries, or searchable representations from video
• Experience with multimodal foundation models, temporal video understanding, re-identification, or vector retrieval
• Experience improving precision/recall, reducing false alerts, or evaluating customer-facing camera AI
• Experience with smart home, security camera, IoT, edge/cloud, or real-time inference architectures
• Experience with Docker, Kubernetes, GCP/AWS, or production model monitoring