Data Scientist

About The Role

Consultant / Data Scientist / GenAI Engineer

Analytics & GenAI delivery team

premier engineering institutes

2–3 years of relevant experience

Key Responsibilities

• Develop and maintain Python-based applications, AI/ML models, and data processing pipelines for GenAI projects.
• Implement Large Language Model (LLM) integrations, including Retrieval-Augmented Generation (RAG) pipelines and embedding-based search solutions.
• Build data ingestion and transformation workflows, working with structured and unstructured datasets.
• Optimize AI model performance through prompt engineering, fine-tuning, and evaluation techniques.
• Collaborate closely with senior team members to translate business requirements into technical solutions.
• Integrate AI solutions with vector databases (e.g., Cosmos DB, Pinecone, ChromaDB) and API-driven applications.
• (Optional) Contribute to cloud-native deployments and Azure architecture–based solutions, including containerization, CI/CD, and basic MLOps workflows.
• Document workflows, maintain code repositories, and follow Agile development practices.
  

Required Qualifications

• 2–3 years of relevant experience in AI/ML development, preferably in enterprise projects.
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field from a premier engineering institute.
• Proficiency in Python programming and familiarity with relevant libraries (e.g., LangChain, Hugging Face, Pandas, NumPy).
• Hands-on experience implementing RAG pipelines, embeddings, and vector search solutions.
• Understanding of LLM architectures and integration patterns.
• Working knowledge of SQL and data processing best practices.
• Basic knowledge of cloud DevOps concepts, preferably with Azure (AWS/GCP experience is also acceptable).
  

Preferred Skills

• Exposure to agentic AI frameworks such as LangGraph, Semantic Kernel, or similar.
• Familiarity with ML model lifecycle management and deployment workflows.
• Prior experience working with cross-border teams and Agile environments.