Sr Software Engineer, Video Intelligence
About The Position
Vivint pioneers cutting-edge smart home security solutions, empowering customers to live a safer, smarter, and more sustainable life. We seek passionate, innovative engineers eager to transform the daily lives of millions through groundbreaking solutions. We blend intelligent hardware, real-time sensor data, and AI to transform how people interact with their homes. We are seeking a Sr Video Intelligence Engineer to advance video understanding. This role will build video-language, summarization, context, and event-reasoning capabilities that improve camera intelligence and customer trust. In this role, you will be responsible to: 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
Nice To Haves
- 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
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.
Benefits
- medical
- vision
- dental
- 401K
- flexible spending accounts
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What This Job Offers
Job Type
Full-time
Career Level
Senior
