AI/ML Engineering (Noida)

Key Skills: Python, AI/ML, Generative AI, LLMs, NLP, RAG, Agentic AI, LangChain, LangGraph, Machine Learning, CI/CD, Microservices, Data Pipelines Roles & Responsibilities: Lead end-to-end AI/ML solution development from problem definition to production deployment.Design, build, and optimize LLM-based, RAG, and Agentic AI and evaluate machine learning models using industry-standard metrics.Implement AI services, APIs, microservices, and scalable data pipelines.Build production-ready AI platforms with CI/CD, monitoring, and observability.Apply Responsible AI principles, including bias, fairness, explainability, and governance.Conduct model performance analysis, drift detection, retraining, and continuous improvement.Collaborate with business, infrastructure, and engineering teams to deliver enterprise AI solutions.Drive architecture decisions and technical leadership for AI/ML engineers and promote best practices in AI engineering and MLOps.Experience Required: 10-15 years of overall experience with 8 years in AI/ML Engineering.Strong expertise in NLP, LLMs, Generative AI, RAG, and Agentic AI.Hands-on experience with LangChain, LangGraph, AutoGen, or similar AI orchestration frameworks.Deep understanding of machine learning, statistics, probability, optimization, and deep learning.Experience evaluating models using Precision, Recall, F1 Score, ROC-AUC, and related metrics.Strong Python programming skills with experience building APIs and microservices.Experience developing production-grade AI services, data pipelines, and CI/CD workflows.Knowledge of Responsible AI, bias mitigation, explainability, and governance frameworks.Experience with MS SQL is an added advantage.Education: Any Graduation Key Skills: Python, AI/ML, Generative AI, LLMs, NLP, RAG, Agentic AI, LangChain, LangGraph, Machine Learning, CI/CD, Microservices, Data Pipelines Roles & Responsibilities: Lead end-to-end AI/ML solution development from problem definition to production deployment.Design, build, and optimize LLM-based, RAG, and Agentic AI and evaluate machine learning models using industry-standard metrics.Implement AI services, APIs, microservices, and scalable data pipelines.Build production-ready AI platforms with CI/CD, monitoring, and observability.Apply Responsible AI principles, including bias, fairness, explainability, and governance.Conduct model performance analysis, drift detection, retraining, and continuous improvement.Collaborate with business, infrastructure, and engineering teams to deliver enterprise AI solutions.Drive architecture decisions and technical leadership for AI/ML engineers and promote best practices in AI engineering and MLOps.Experience Required: 10-15 years of overall experience with 8 years in AI/ML Engineering.Strong expertise in NLP, LLMs, Generative AI, RAG, and Agentic AI.Hands-on experience with LangChain, LangGraph, AutoGen, or similar AI orchestration frameworks.Deep understanding of machine learning, statistics, probability, optimization, and deep learning.Experience evaluating models using Precision, Recall, F1 Score, ROC-AUC, and related metrics.Robust Python programming skills with experience building APIs and microservices.Experience developing production-grade AI services, data pipelines, and CI/CD workflows.Knowledge of Responsible AI, bias mitigation, explainability, and governance frameworks.Experience with MS SQL is an added advantage.Education: Any Graduation Key Skills: Python, AI/ML, Generative AI, LLMs, NLP, RAG, Agentic AI, LangChain, LangGraph, Machine Learning, CI/CD, Microservices, Data Pipelines Roles & Responsibilities: Lead end-to-end AI/ML solution development from problem definition to production deployment.Design, build, and optimize LLM-based, RAG, and Agentic AI and evaluate machine learning models using industry-standard metrics.Implement AI services, APIs, microservices, and scalable data pipelines.Build production-ready AI platforms with CI/CD, monitoring, and observability.Apply Responsible AI principles, including bias, fairness, explainability, and governance.Conduct model performance analysis, drift detection, retraining, and continuous improvement.Collaborate with business, infrastructure, and engineering teams to deliver enterprise AI solutions.Drive architecture decisions and technical leadership for AI/ML engineers and promote best practices in AI engineering and MLOps.Experience Required: 10-15 years of overall experience with 8 years in AI/ML Engineering.Strong expertise in NLP, LLMs, Generative AI, RAG, and Agentic AI.Hands-on experience with LangChain, LangGraph, AutoGen, or similar AI orchestration frameworks.Deep understanding of machine learning, statistics, probability, optimization, and deep learning.Experience evaluating models using Precision, Recall, F1 Score, ROC-AUC, and related metrics.Strong Python programming skills with experience building APIs and microservices.Experience developing production-grade AI services, data pipelines, and