MLOps Engineer
Core
Designing, implementing, and managing the end-to-end lifecycle of machine learning models for 2K's global video game titles, focusing on automated systems for training, deployment, monitoring, and retraining at scale.
Role type
Senior MLOps Engineer
Builds
Automated ML pipelines, scalable model serving infrastructure, and centralized feature stores for in-game personalization and player behavior adaptation.
Domain
Video Games / Machine Learning Infrastructure
Deliverable
production ML models
Required skills
Python, SQL, Spark/PySpark, Docker, Kubernetes, CI/CD, Airflow, MLflow, Kubeflow, AWS SageMaker, Databricks
Preferred skills
Real-time inference for high-concurrency applications, Data Privacy regulations (GDPR/CCPA), Reinforcement Learning, Recommendation Systems
Technologies
Databricks, MLflow, Kubeflow, AWS SageMaker, Seldon, PyTorch, TensorFlow, Scikit-Learn
Responsibilities
Lead design and maintenance of end-to-end ML pipelines covering data ingestion, feature engineering, model training, and deployment; Architect and manage scalable model serving infrastructure; Implement and maintain a centralized feature store; Develop and optimize Continuous Training (CT) pipelines; Implement specialized monitoring for ML assets tracking model drift and feature skew; Partner with Data Scientists to refactor experimental code into production-ready components; Manage and optimize infrastructure costs of GPU/CPU clusters.
Seniority
Senior, hands-on IC