Machine Learning Engineer

Role - Machine Learning Engineer Experience Required -8+ Years We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph. Must Have Technical/Functional Skills: We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph. • Implement short-term and long-term memory strategies for LLM-based systems. • Optimize prompts, retrieval pipelines, and orchestration logic. • Collaborate with product and platform teams to deliver scalable AI solutions. Required Qualifications • Strong experience with LLMs (e.g., OpenAI, Anthropic, Llama, Mistral) • Hands-on experience with LangChain and/or LangGraph. • Solid understanding of LLM memory architecture and state management. • Proficiency in Python and ML engineering best practices. Nice to Have • Experience with GCP services (e.g., Vertex AI, BigQuery, GCS). • Experience deploying ML/GenAI systems in production environments. • data scientist • Can do ML model Roles & Responsibilities • Design, develop, and deploy GenAI applications using LLMs. • Build and implement agentic workflows using LangChain/LangGraph. • Develop ML models and production-ready AI solutions. • Implement and manage LLM memory and state management strategies. • Optimize prompts, retrieval pipelines, and orchestration workflows. • Collaborate with product and platform teams to deliver scalable AI solutions. • Deploy, monitor, and maintain AI/ML systems in production environments. • Evaluate and integrate open-source and proprietary LLMs. Show more Show less