Sr. Principal Machine Learning Engineer - Central Product Insights

Los Angeles · 3+ years experience · Posted Sep 30, 2026

At a glance

As a Sr. Principal ML Engineer within the Central Product team, you will define and drive the modeling architecture that powers personalization, matchmaking, and social experiences across the player ecosystem.
You will lead the AI and modeling layer that transforms foundational data systems into intelligent, adaptive, and fair experiences for players.

Define and lead the modeling architecture that powers player personalization, matchmaking, social graph recommendations, and community discovery.
Develop models for churn model, revival models.
Drive multi-objective optimization frameworks balancing fairness, latency, diversity, and experience quality.
Establish and standardize evaluation protocols (match quality, satisfaction metrics, toxicity mitigation).
Build real-time inference systems for personalized content, store offers, matchmaking and player interactions at scale.
Partner with the Data Engineers to integrate low-latency data pipelines and feature stores into online model serving.
Lead adoption of contextual bandits, reinforcement learning, and graph ML for adaptive, session-aware personalization.
Define Responsible AI standards for matchmaking and social systems — including fairness, transparency, and explainability.
Drive org-wide model optimization standards - latency, throughput, memory efficiency.
Mentor senior ML engineers and data scientists, strengthening system design and experimentation practices.

15+ years in Machine Learning or Applied AI; 3+ years in a principal or staff-level technical leadership role.
Proven experience in real-time, large-scale ML systems - matchmaking, recommendations, or personalization.
Deep expertise in graph ML, reinforcement learning, and representation learning.
Proficiency in PyTorch, TensorFlow, JAX, and modern data/serving frameworks (Ray, Kafka, Flink, Redis).
Strong understanding of A/B testing, experiment design, and player experience metrics.
Track record of defining cross-team ML standards and leading technical direction.