Key skills
PythonSQLAIMLDeep LearningGenAIRAGAgenticData EngineeringAnalyticsCI/CDCommunication
About this role
Vivint is a company focused on creating personalized AI experiences for households. They are seeking a Senior AI Experience Engineer to design and build systems that enhance personalization and recommendations based on user behavior and context.
Responsibilities:
- Design and build personalization, recommendation, ranking, retrieval, candidate-generation, and re-ranking systems
- Develop household, user, device, event, and context representations using behavioral signals, embeddings, feedback, and product telemetry
- Build feedback loops from searches, dismissals, saves, notification engagement, customer actions, and product usage
- Partner with Agentic AI and AI Platform teams to connect short-term context, long-term memory, retrieval, and personalization
- Design experiments with Product and Analytics, including A/B tests, holdouts, interleaving experiments, contextual bandits, multi-armed bandits, or causal measurement where appropriate
- Deploy and monitor production recommendation systems with attention to latency, reliability, cost, privacy, and customer trust
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 ranking, retrieval, recommendation, personalization, or learning-to-rank systems
- Strong Python, SQL, data engineering, and production ML skills
- Experience with embeddings, behavioral datasets, online/offline evaluation, and experimentation
- Experience deploying ML systems into production with CI/CD and monitoring
- Strong communication skills and ability to partner with product, analytics, design, and engineering teams
- Experience with collaborative filtering, content-based recommendations, two-tower models, sequence models, or deep learning recommenders
- Experience with feature stores, vector retrieval, model serving, contextual bandits, or reinforcement learning
- Experience optimizing engagement, retention, click stream, notification relevance, customer satisfaction, or conversion metrics
- Experience with GenAI recommenders, RAG, AI memory, or agentic personalization
- Experience with smart home, IoT, security, energy, mobile, or device telemetry data