Data Scientist / AI/ML Engineer / GenAI Engineer

Role Overview

MCube AI Pvt. Ltd. is looking for a Data Scientist / AI/ML Engineer / GenAI Engineer with 3–4 years of experience in building, deploying, and maintaining production-ready AI/ML applications. The ideal candidate should have strong Python and software engineering skills, hands-on experience with RAG architectures, and a good understanding of AI system design, evaluation, and optimization.

Responsibilities

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

Requirements

• 3–4 years of experience in AI/ML application development
• Strong Python
• Strong software engineering fundamentals
• AI system design, evaluation, monitoring, and performance optimization
• Production AI application development and deployment
• Clean code, modular design, debugging, and testing
• RAG Architectures
• TensorFlow / PyTorch / Scikit-learn
• NLP concepts
• API development and integration
• Ability to work independently and collaboratively
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related quantitative field.

Skills

• Python
• RAG Architectures
• PyTorch
• TensorFlow
• Scikit-learn

Nice to Have

• Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB
• Cloud: AWS, Azure, GCP
• Docker and deployment pipelines
• FinTech domain experience