AI Media Personalization Engineer.

Core skills include recommendation system architectures (collaborative filtering, matrix factorization, deep learning recommenders), A/B testing at scale, feature engineering from user behavior data, and real-time serving infrastructure. Understanding of multi-armed bandits for exploration, contextual bandits for cold start, and graph-based approaches for social recommendations is increasingly expected.

This is an active area of focus. Engineers design multi-objective systems that optimize for user satisfaction, content diversity, and creator fairness alongside engagement. Techniques include diversity-aware recommendation, filter bubble detection, and user control mechanisms. Regulatory attention on algorithmic recommendation makes responsible personalization both an ethical imperative and a business requirement.

Ask about equity structure, vesting schedule, annual bonus targets, 401(k) match, health insurance premiums, PTO policy, and remote flexibility. Equity at media and streaming companies adds $20,000 to $80,000 annually. In Richmond's market, these extras can add $36,250 or more on top of the base salary.

Compensation scales with expertise in recommendation systems, content understanding, and user modeling at scale. Engineers who can improve engagement metrics through personalized content experiences earn premiums. Experience with collaborative filtering, content-based recommendations, and multi-objective optimization (engagement vs. diversity vs. revenue) is highly valued. In Richmond, these factors can push compensation from the 25th percentile of $112,000 to the 75th percentile of $184,000 or beyond.

Richmond combines a strong government and defense sector with growing technology and financial services industries. Capital One's headquarters drives significant fintech employment. For AI Media Personalization Engineers specifically, the median salary of $145,000 reflects that demand.

Remote work has compressed geographic salary premiums for AI Media Personalization Engineers. Some Richmond employers offer location adjusted pay, while others maintain local rates to attract in office talent. In Richmond's moderate cost market, remote and local salaries are converging. The $112,000 to $184,000 range reflects both arrangements.

Richmond combines a strong government and defense sector with growing technology and financial services industries. Capital One's headquarters drives significant fintech employment. For AI Media Personalization Engineers specifically, compensation scales with expertise in recommendation systems, content understanding, and user modeling at scale, which signals sustained demand. The current compensation range of $112,000 to $184,000 reflects a market that is competing for talent.