Data Scientist / AIML Engineer / Gen AI Engineer

Job Title: Data Scientist / AIML Engineer / Gen AI Engineer Location: Gurugram, Haryana (On-site, 5 days a week) Experience: 3 – 4 Years Compensation: ₹15,00,000 – ₹25,00,000 LPA Employment Type: Full-Time

About the Role: We are a fast-growing, product-based technology firm seeking a highly skilled AI/ML professional to join our newly established AI division. You will be instrumental in designing, deploying, and maintaining production-grade AI applications, focusing on scalable Gen AI and Machine Learning systems.

Key Responsibilities:

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  Design scalable, reliable AI systems with a focus on production readiness, maintainability, and performance.

  
  


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  Create and maintain Retrieval-Augmented Generation (RAG) pipelines and AI agent frameworks.

  
  


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  Design reliable LLM workflows using structured outputs, validation, retrieval, and business rules.

  
  


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  Perform data analysis, model evaluation, root cause analysis, and performance optimization.

  
  


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  Develop APIs and integrate AI solutions into existing products and platforms.

  
  


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  Develop automated evaluation, validation, and testing strategies for AI applications.

  
  


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  Collaborate with cross-functional teams and business stakeholders to define and deliver AI solutions.

  
  

Must-Have Qualifications:

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  3–5 years of experience building AI/ML applications as an Individual Contributor.

  
  


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  Full-time Bachelor's or Master’s degree in Computer Science, AI, ML, Data Science, or a related quantitative field (Distance education is not accepted).

  
  


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  Strong proficiency in Python and robust software engineering fundamentals (clean code, modular design, debugging, and testing).

  
  


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  Hands-on experience with RAG architectures and NLP concepts.

  
  


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  Practical experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.

  
  


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  Familiarity with API development and system integration.

  
  

Good-to-Have Skills:

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  Experience with Vector Databases (Pinecone, Weaviate, FAISS, ChromaDB).

  
  


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  Knowledge of Cloud platforms (AWS, Azure, GCP) and deployment pipelines (Docker).

  
  


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  Exposure to Fintech products, platforms, or domain-specific use cases.