Key Responsibilities

• Design, develop, and deploy AI/ML solutions to solve business problems across operations, manufacturing, supply chain, and enterprise applications.
• Build production-grade applications using Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI agents, and modern AI frameworks.
• Develop and optimize machine learning, computer vision, NLP, and predictive analytics models based on business requirements.
• Collaborate with Product Managers and business stakeholders to understand problems, identify AI opportunities, and translate them into scalable solutions.
• Prepare, clean, and engineer datasets for training, evaluation, and production deployment.
• Build APIs and AI services that integrate seamlessly with web applications, mobile applications, ERPs, and enterprise systems.
• Evaluate emerging AI models, frameworks, and technologies to continuously improve solution quality and business impact.
• Monitor model performance, accuracy, latency, and reliability, and continuously improve deployed AI systems.
• Document AI architectures, experiments, and deployment pipelines while following engineering best practices.

Qualifications & Skills Required

Education

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field (B.Tech./B.E. preferred).

Experience

• 1–3 years of experience developing AI/ML applications in production environments.
• Strong hands-on experience with Python (mandatory).
• Experience with machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, or XGBoost.
• Experience building applications using modern LLMs (OpenAI, Claude, Gemini, Llama, etc.).
• Hands-on experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
• Strong SQL skills and experience working with structured and unstructured datasets.
• Experience building REST APIs using FastAPI, Flask, or similar frameworks.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.

Technical Skills

• Python
• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Retrieval Augmented Generation (RAG)
• AI Agents
• Prompt Engineering
• NLP
• Computer Vision
• Vector Databases
• SQL
• Git
• Docker
• API Development

Preferred Qualifications

• Experience deploying AI solutions into production environments.
• Experience with OCR, document intelligence, or multimodal AI systems.
• Experience with computer vision applications using OpenCV, YOLO, or related frameworks.
• Familiarity with MLOps tools such as MLflow, Airflow, Kubeflow, or similar platforms.
• Experience working with manufacturing, logistics, industrial automation, or supply chain datasets.
• Exposure to IoT, robotics, or sensor data is an added advantage.

What We’re Looking For

• Strong analytical and problem-solving skills with a first-principles approach.
• Curiosity to experiment with emerging AI technologies while maintaining engineering discipline.
• Ability to independently own AI projects from idea to production deployment.
• Strong communication skills and the ability to explain AI concepts to non-technical stakeholders.
• Passion for building practical AI solutions that create measurable business impact rather than proof-of-concepts.