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Posted 28 days ago

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AIML Architect

BengaluruOn-siteFull-time

AI Summary

This role is for one of the Weekday's clientsSalary range: Rs 5000000 - Rs 6000000 (ie INR 50-60 LPA)Min Experience: 12+ yearsLocation: Bengaluru, HyderabadJobType: full-timeRequirementsPrincipal AIML Architect● Over 12 years of experience in software engineering, including more than 8 years focused on AI/ML systems● Proficient in Python with practical expertise in managing the complete ML lifecycle● Essential: Expertise in architectural design and process workflows for building scalable AI/ML s

About this role

This role is for one of the Weekday's clients

Salary range: Rs 5000000 - Rs 6000000 (ie INR 50-60 LPA)

Min Experience: 12+ years

Location: Bengaluru, Hyderabad

JobType: full-time

Requirements

Principal AIML Architect

● Over 12 years of experience in software engineering, including more than 8 years focused on AI/ML systems

● Proficient in Python with practical expertise in managing the complete ML lifecycle

● Essential: Expertise in architectural design and process workflows for building scalable AI/ML systems

● Develop Generative AI solutions such as LLMs, Retrieval-Augmented Generation (RAG), and multi-agent frameworks

● Build, train, fine-tune, and enhance ML and LLM models for optimal performance

● Implement MLOps practices including CI/CD pipelines, monitoring, model retraining, and drift detection

● Hands-on experience with frameworks and libraries like PyTorch, TensorFlow, scikit-learn, LangChain, and LlamaIndex

● Work extensively with vector databases such as FAISS, Pinecone, and Milvus, as well as embedding techniques

● Deploy solutions via APIs, batch processing, and streaming across cloud platforms including AWS, Azure, and GCP

● Provide mentorship to teams, engage collaboratively with stakeholders, and lead innovation initiatives

Required Skills: Python, AI/ML System Architecture and Design, Scalable Process Workflows, Production-level ML Development, Large Language Models and Generative AI, RAG Pipelines, Prompt Engineering, Model Training and Optimization, MLOps (CI/CD, Monitoring, Drift Detection), Model Deployment (API/Batch/Streaming), PyTorch, TensorFlow, scikit-learn, LangChain, LlamaIndex, Vector Databases (FAISS, Pinecone, Milvus), Embeddings and Retrieval Systems, Cloud Platforms (AWS, Azure, GCP), Scalable System Architecture, SQL and NoSQL Databases

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