Lead ML Ops Engineer

• 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

• 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:
  

• 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.
  

• 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.