Data Scientist

Role Overview

We are looking for a professional with 3–4 years of experience building AI/ML applications with strong Python and software engineering skills to design and maintain production-ready AI systems.

Responsibilities

• Design scalable, reliable AI systems with a focus on production readiness, maintainability, and performance.
• Perform root cause analysis and debugging of AI pipelines to improve accuracy, consistency, and reliability.
• Develop automated evaluation, validation, and testing strategies for AI applications.
• Design reliable LLM workflows using structured outputs, validation, retrieval, and business rules.
• Create and maintain RAG pipelines and AI agent frameworks.
• Perform data analysis, model evaluation, and performance optimization.
• Develop APIs and integrate AI solutions into existing products and platforms.
• Collaborate with cross-functional teams to define AI use cases and deliver solutions.
• Monitor, troubleshoot, and continuously improve deployed AI systems.

Requirements

• 3–4 years of experience building AI/ML applications.
• Strong proficiency in Python.
• Hands-on experience with AI system design, evaluation, monitoring, and performance optimization.
• Experience developing, deploying, and maintaining production AI applications.
• Strong software engineering fundamentals, including clean code, modular design, debugging, and testing.
• Experience with RAG architectures.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Good understanding of NLP concepts.
• Familiarity with API development and integration.
• Experience with vector databases such as Pinecone, Weaviate, FAISS, or ChromaDB.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker and deployment pipelines.

Skills

• Python
• PyTorch
• TensorFlow
• AWS
• Docker

Benefits

• Provident Fund