Intelligent Systems Architect (RL)/Lead RL Systems Engineer (Telangana)

Required Skills/Role expectation - Robust understanding of reinforcement learning systems (training loops, reward design, simulation environments) Experience designing end-to-end AI/ML architectures (data model decision systems) Define architecture for simulation, training, and real-time inference layers Ensure seamless integration with TUI data, pricing, and booking platforms Design for scalability, modularity, and future extensibility Embed governance, explainability, and control mechanisms in RL systems Establish architecture standards, patterns, and best practices Integration with enterprise platforms, APIs, and data ecosystems Experience with real-time decisioning systems and event-driven architectures - Design and build end-to-end RL pipelines (simulation, training, deployment, inference) Integrate RL models with simulators, data platforms, and production systems Optimize systems for performance, scalability, and low-latency decisioning Implement A/B testing, experimentation frameworks, and rollout strategies Ensure reliability, monitoring, and continuous improvement of RL systems Hands-on experience with reinforcement learning frameworks and training pipelines Understanding of simulation environments, reward tuning, and policy optimization Strong in Python / ML engineering stacks Scalable system design using microservices and distributed systems Cloud platforms (AWS), containerization (Docker/Kubernetes) .