Machine Learning Engineer

Riot has petabytes of data and state-of-the-art processing technologies to build products that elevate the player experience at a massive scale.

• Define and lead the modeling architecture that powers player personalization, matchmaking, social graph recommendations, and community discovery.
• Develop models for churn and revival.
• 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 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.
• Drive experimentation systems for live-service optimization (player retention, engagement, satisfaction).
• Work with Product leaders, Software Engineers & Data Engineers to define data schema, pipeline, and feature requirements.
• Co-define standards for data schema design, feature lineage, and model observability.
• Define Responsible AI standards for matchmaking and social systems — fairness, transparency, explainability.
• Implement bias mitigation and trust calibration mechanisms.
• Drive org-wide model optimization standards — latency, throughput, memory efficiency.
• Architect systems for multi-model orchestration.
• Define telemetry standards for online model observability and drift detection.
• Mentor senior ML engineers and data scientists.

• 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.
• Desired: background in game development, player behavior modeling, or social ecosystems.
• Desired: experience in trust & safety, toxicity detection, or community health models.
• Desired: familiarity with Vertex AI, SageMaker, or internal orchestration systems for real-time inference.
• Desired: success integrating ML systems with live-service game backends.

• Riot focuses on work/life balance, open paid time off policy, flexible work schedules.
• Medical, dental, and life insurance, parental leave, 401k with company match.