Sr Software Engineer, AI Experience

NRG Energy is seeking a Sr AI Experience Engineer to build personalization and recommendation systems that enhance Vivint AI experiences for households. The role involves designing and implementing advanced systems, collaborating with various teams, and ensuring the reliability and effectiveness of deployed solutions.

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