Data Scientist

10 - 14 years

0 Lacs

Posted:7 hours ago| Platform: Naukri logo

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About the Role:

We are seeking a highly skilled and experienced Senior Data Science & ML Engineer to join our innovative AI team. This role is perfect for who is passionate about building intelligent, production-ready AI systems, with a particular emphasis on Generative AI, Large Language Models (LLMs), and Agentic AI.

Key Responsibilities:

  • Generative AI & LLM Systems: Design, develop, and deploy end-to-end Generative AI applications, with a strong focus on LLMs.
  • Agentic AI & Orchestration: Lead the development of complex, multi-agent AI systems and sophisticated workflows using frameworks like LangChain and LangGraph.
  • Retrieval Augmented Generation (RAG): Architect and implement robust RAG pipelines for enhanced LLM applications, including vector database integration and content retrieval optimization.
  • Prompt Engineering Expertise: Develop and implement advanced prompt engineering strategies to optimize LLM performance, reliability, and precision for various tasks.
  • LLM Fine-tuning & Customization: Perform large-scale fine-tuning and adaptation of open-source and proprietary LLMs for domain-specific applications and improved performance.
  • Machine Learning Model Development: Design, train, test, and validate ML models for a wide range of tasks, including but not limited to Computer Vision (e.g., object detection, image classification, segmentation) and Natural Language Processing (e.g., text classification, sentiment analysis, entity recognition). 
  • MLOps & Deployment: Build and maintain scalable and reliable production pipelines for ML models and LLM applications, ensuring seamless integration and deployment.

Required Skills & Qualifications:

  • Experience: 4-5 years of hands-on experience in Data Science, Machine Learning Engineering, or a related field, with a strong portfolio of deployed solutions.
  • Programming: Python
  • Generative AI & LLMs: Generative AI, LLMs
  • AI Orchestration: LangChain, LangGraph, Agentic AI
  • LLM Techniques: RAG (Retrieval Augmented Generation), Prompt Engineering, LLM Finetuning
  • ML Domains: Natural Language Processing (NLP), Computer Vision
  • ML Lifecycle: End-to-end ML Model Lifecycle management
  • API Development: Flask, FastAPI
  • Containerization: Docker
  • Rapid Prototyping: Streamlit
  • Problem-Solving: Excellent analytical and problem-solving skills.

Preferred Skills (Nice-to-Haves):

  • Experience with cloud platforms (AWS, Azure, GCP) and their respective AI/ML services (e.g., SageMaker, Azure ML, Vertex AI).
  • Familiarity with MLOps tools and practices beyond Docker (e.g., Kubernetes, MLflow, CI/CD pipelines).
  • Contributions to open-source projects or relevant publications in AI/ML conferences.
  • Knowledge of vector databases (e.g., Pinecone, Weaviate, Milvus)

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