Responsibilities: • ML System Development: Design, develop, and maintain scalable and efficient machine learning systems, including writing ML services and APIs. • Model Deployment: Implement and manage the deployment of machine learning models, including transformer based LLMs, into production environments, ensuring reliability and scalability. • Infrastructure Management: Collaborate with infrastructure teams to optimize and manage the underlying systems supporting machine learning workflows. • Data Pipeline Creation: Create robust and efficient data pipelines for collecting, processing, and preparing datasets for machine learning models. • Collaboration: Work closely with data scientists, researchers, and cross-functional teams to integrate ML solutions into existing software infrastructure. • Performance Optimization: Continuously optimize and improve the performance of machine learning algorithms and systems. • Documentation: Develop and maintain documentation for machine learning systems, APIs, and data pipelines to ensure clarity and ease of use for team members. Our ideal candidates would: • 3+ years of experience including working on designing multi-component systems • Strong grasp of one high-level language like Python. • General awareness of SQL and database design concepts • Solid understanding of testing fundamentals • Strong communication skills • should have prior experience in managing and executing technology products. • Decent understanding of various Gen AI based ML approaches • Experience in building agentic architectures using langgraph or similar libraries Bonus: • Prior experience working with high-volume, always-available web-applications • Experience working with cloud • Knowledge of cloud platforms such as AWS, GCP, or Azure. • Experience with deploying small and big open source LLMs in production environments using containerization tools like Docker • Experience in Distributed systems. • Experience working with Start-up is a plus point.