Develop, test, and implement machine learning models for business and product use cases.
Build AI-powered applications using Python, machine learning libraries, and relevant AI frameworks.
Work with Large Language Models (LLMs), prompt engineering, embeddings, and Retrieval-Augmented Generation (RAG).
Assist in developing AI agents and intelligent workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent tools.
Perform data preprocessing, feature engineering, model training, validation, and performance evaluation.
Integrate AI/ML models into applications using REST APIs and backend services.
Work with vector databases and document retrieval systems to support LLM-based applications.
Troubleshoot model performance issues and improve accuracy, reliability, and response times.
Write clean, reusable, maintainable, and well-documented code.
Collaborate with senior developers, product managers, and cross-functional teams to deliver AI-driven features.
Participate in code reviews, testing, debugging, and continuous improvement of AI applications.
Research emerging AI/ML tools and techniques and contribute to the adoption of relevant technologies.
2–4 years of hands-on experience in AI/ML development or a closely related field.
Strong proficiency in Python and familiarity with libraries such as NumPy, Pandas, and Scikit-learn.
Good understanding of machine learning algorithms, model training, validation, and evaluation techniques.
Practical exposure to Generative AI, LLMs, prompt engineering, and building AI-powered applications.
Familiarity with RAG pipelines, embeddings, and vector databases.
Experience with at least one deep learning framework, such as PyTorch or TensorFlow.
Familiarity with AI/ML frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent tools.
Experience developing or integrating REST APIs.
Working knowledge of Git, software development practices, and debugging techniques.
Strong analytical, problem-solving, and communication skills.
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