Sr Software Engineer, Video Intelligence
About The Position
NRG/Vivint is seeking a Sr Video Intelligence Engineer to advance video understanding and improve camera intelligence and customer trust. The role builds video-language, summarization, context, and event-reasoning capabilities. It owns VLM strategy, video-language understanding, temporal video reasoning, event understanding, and multimodal embeddings; improves AI Video Search, video summarization, alert relevance, recognition support, and false-alert reduction; and develops systems that generate useful natural-language descriptions, insights, and summaries from video. The engineer partners with AI, platform, product, and app teams to move models from research into production, develops production evaluation methods, and guides architecture decisions across cloud, edge, and hybrid inference paths. The position requires in-office presence in Seattle, Washington on a hybrid schedule: in office Monday through Thursday and work from home Friday. It will start remote and then move to the hybrid schedule. The base salary range is $190,000 to $207,000. Actual salaries vary based on factors including location, experience, and performance. The position may be eligible for annual bonus, short- and long-term incentives, program-specific awards, and benefits including medical, vision, dental, 401(k), and flexible spending accounts.
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 a master’s degree in one of those fields and 2+ years of such experience.
- 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 insurance
- Vision insurance
- Dental insurance
- 401(k)
- Flexible spending accounts
- Annual bonus may be available
- Short- and long-term incentives may be available
- Program-specific awards may be available
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What This Job Offers
Job Type
Full-time
Career Level
Senior
