Data Scientist (Klo Job No 138)

Job description

Key Responsibilities

• Design and develop LLMpowered applications using frameworks such as LangChain, AutoGen, LangGraph, and CrewAI
• Build RetrievalAugmented Generation (RAG) pipelines using embeddingbased semantic search and external/vector databases
• Develop chatbased AI systems including:
  • Chat with documents (PDFs, CSVs, KBs)
  • Chat with databases (NL SQL)
  • ChatGPTlike internal assistants
• Engineer and optimize prompt strategies, task decomposition, and multiagent workflows
• Finetune, evaluate, and optimize opensource and proprietary LLMs for domainspecific applications
• Deploy and scale AI systems using AWS, Docker, Kubernetes, and MLflow
• Integrate AI services with backend systems via APIs and middleware
• Ensure performance, scalability, interpretability, and ethical AI compliance
• Collaborate with product, business, and client stakeholders to translate requirements into AI solutions

Required Skills

Programming & Frameworks

• Strong proficiency in Python
• Experience with PyTorch, TensorFlow, Scikitlearn
• Experience with Hugging Face Transformers

Generative AI & LLMs

• Handson experience with LLMs (OpenAI, HuggingFace, Bedrock)
• Prompt engineering and response optimization
• Tokenization, embeddings, semantic similarity, and reranking strategies

RAG & Agentic Systems

• Proven experience building RAG pipelines
• Experience with LangChain, CrewAI, AutoGen, or LangGraph
• Knowledge of embeddings, chunking strategies, and vector search

Cloud & MLOps

• Experience with AWS (EC2, Lambda, SageMaker, S3, Bedrock)
• Docker & Kubernetes for deployment
• ML lifecycle and observability using MLflow
• Experience in deploying production ML/LLM systems

Additional Strengths

• Strong understanding of NLP techniques
• Experience with Explainable AI (SHAP, LIME)
• Excellent problemsolving and communication skills

Qualifications

• Bachelors degree in Computer Science, Electronics, AI/ML, or related field
• 4+ years of experience in AI/ML or Generative AI engineering
• Certifications or handson projects in LLMs, GenAI, NLP, or MLOps are a plus
• Research or publication experience is an added advantageRole & responsibilities