Data Scientist

About the Role

Consultant / Data Scientist / GenAI Engineer

premier engineering institutes

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.