Data Scientist

Hiringhood; Gurugram District; On-site; INR 1,000,000 - 1,400,000; Full time

Job summary

Hiringhood is seeking an AI/ML engineer in Gurugram with 3–4 years of hands-on Python and software engineering experience. You will contribute to building, deploying, and maintaining production AI applications, focusing on scalable NLP-enabled solutions and robust system design.

Applicants should be proficient in Python, familiar with ML frameworks like TensorFlow, PyTorch, or Scikit-learn, and comfortable collaborating with cross-functional teams to deliver reliable AI capabilities.

Qualifications

• 3–4 years of experience building AI/ML applications with strong Python and software engineering skills.
• Proficiency in Python and hands-on experience with AI system design, evaluation, monitoring, and performance optimization.
• Experience developing, deploying, and maintaining production AI applications and strong software engineering fundamentals.

Skills

Python

AI/ML development

API development

NLP concepts

Software engineering fundamentals

Team collaboration

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Job description

• 3–4 years of experience building AI/ML applications with strong Python and software engineering skills.
• Strong proficiency in Python.
• Hands-on experience with:
• Understanding of 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 machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Good understanding of NLP concepts.
• Familiarity with API development and integration.
• Ability to work independently as well as in collaborative team environments.

Good to have

• Experience with vector databases such as Pinecone, Weaviate, FAISS, ChromaDB.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, and deployment pipelines.
• Exposure to fintech products, platforms, or domain-specific use cases.
• 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 including engineering, and business stakeholders to define AI use cases and deliver solutions.
• Monitor, troubleshoot, and continuously improve deployed AI systems.