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 Google Cloud Platform 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.
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