Lead ML Ops Engineer

Job Summary We are looking for a Lead ML Platform / MLOps Engineer to build and scale the infrastructure that powers AI across PlaySimple. You will design, develop, and operate the platforms that enable Data Scientists to rapidly build, deploy, monitor, and continuously improve Machine Learning models in production. You will work closely with Data Science, Platform Engineering, and Product teams to build a world-class AI platform supporting experimentation, personalization, and intelligent decision-making at scale. Responsibilities Design and build scalable ML infrastructure supporting training, deployment,monitoring, and governance. Develop CI/CD pipelines for Machine Learning workflows. Build reliable model serving and inference platforms. Develop feature stores, experiment tracking, model registries, and automated deployment pipelines. Optimize large-scale data processing pipelines using Apache Spark. Build infrastructure supporting LLM applications and Agentic AI workflows. Partner with Data Scientists to productionize Machine Learning models. Improve platform observability, reliability, scalability, and developer productivity. Drive engineering best practices across the ML platform. Requirements Requirements 5–8 years of experience building Machine Learning platforms or MLOps infrastructure. Demonstrated experience deploying and operating production Machine Learning systems. Strong software engineering skills in Python. Experience with Apache Spark and distributed computing. Strong understanding of modern MLOps practices Experience with: o Docker o Kubernetes o ML deployment frameworks o Feature Stores o Model Registries o Experiment Tracking Familiarity with Agentic AI concepts and orchestration platforms such as n8n. Experience with AWS, Azure, or GCP. Product experience in Gaming, Consumer Internet, E-commerce,Marketplace, or Decision Science platforms. Strong communication and collaboration skills. An avid gamer with a passion for understanding player behaviour and game mechanics. What We Look For Strong engineering fundamentals. Platform-first mindset. Excellent problem-solving ability. Ownership and accountability. Curiosity for modern AI technologies. Ability to collaborate across cross-functional teams. Comfortable working in a fast-paced product environment. Passion for gaming.