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Role: Data Scientist / AI Engineer
Location: Pune
Key Responsibilities:
Build LLM-powered applications using RAG, Agents & fine-tuning
Work with LangChain, LlamaIndex, and GenAI frameworks
Develop ML models (Regression, Classification, Clustering, Time-Series)
Solve real-world problems like churn prediction, forecasting & fraud detection
Handle end-to-end AI lifecycle (data → model → deployment)
Eligibility Criteria:
4+ years of experience in Data Science / ML
Minimum 1+ year hands-on experience in Generative AI / LLMs
Strong understanding of ML algorithms and AI frameworks
Interested candidates can screen their interest by sharing their profile to [HIDDEN TEXT] or contact 9150008614
Kamlax Global Technologies is a leading IT services & business solution provider delivering cutting edge technology solutions to enterprises across the world.
we add value to organizations through a synergy of skills, technology insight, innovation, products and services that orchestrate our customer's business to perfection. Our expertise bridges the gap between the businesses and IT and offers detailed, process-driven solutions enabling our customers to enhance productivity and achieve better ROI.
Job ID: 145787949
Skills:
Prometheus, Neural Networks, Grafana, Deep Learning, Devops, Image Processing, Kubernetes, Generative AI, Data Observability, AI Agents, Chatbots, SRE Observability, Retrieval-Augmented Generation, Event Monitoring System, AWS AI Services, Workflow Integration, Machine Learning Operations
Skills:
BigQuery, DataFlow, Python, Sql, LangChain, LangGraph, Vector Databases, Cloud Functions, Vertex AI
Skills:
Distributed Systems, API design, React, Neo4j, Flask, Redis, FastAPI, Python, Cloud Infrastructure, Docker, tool calling, RAG architecture, agent-based systems, Streamlit, vector search strategies, LLM APIs, PEFT, observability for AI systems, DeepSpeed, async workflows, LoRA, Gradio, Pinecone, model fine-tuning, Accelerate, Hugging Face Transformers, FAISS, prompt engineering, AWS Neptune, Qdrant
Skills:
BigQuery, Data Cleaning, Sql, Docker, Azure, Python, Statistical Analysis, Machine Learning Algorithms, AWS, advanced prompting strategies, embeddings, Agent-to-Agent A2A orchestration, Model Context Protocol MCP, Chain-of-Thought CoT prompting, fine-tuning models, Transformation, large datasets, scalable data processing workflows, GCP Vertex AI, Normalization, LangChain RAG frameworks, NLP techniques, Generative AI LLMs
Skills:
PostgreSQL, Flask, FastAPI, Python, LangChain, automation systems, embeddings, LLMs, SLMs, vector databases, LangGraph, rule-based systems, decision engines, RAG pipelines
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