Data Scientist

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Description

Roles and Responsibilities Develop, maintain and enhance Python-based applications, ML services and AI solutions. Design and implement scalable, reusable and production-ready software components using Python and open-source AI/ML frameworks. Develop and deploy machine learning and deep learning models for real-world business use cases. Work with Generative AI and Large Language Models (LLMs), including RAG, prompt engineering, model evaluation, fine-tuning and knowledge-based AI solutions. Develop AI/ML pipelines for classification, regression, forecasting, NLP and other machine learning use cases. Work with frameworks and libraries such as PyTorch, LangChain, LlamaIndex, Hugging Face, Scikit-learn, Pandas and Spark. Design and implement RAG-based solutions and LLM applications using enterprise and customer-specific data. Develop APIs and microservices for AI/ML solutions using technologies such as FastAPI. Work with structured and unstructured data using RDBMS, NoSQL and distributed data-processing platforms. Develop data processing and engineering pipelines using technologies such as Apache Spark / PySpark. Build and maintain ML training, model evaluation and deployment pipelines. Skills / Requirements Strong hands-on experience with Python. Good understanding of software engineering principles and development of scalable, reusable applications. Experience with REST APIs and/or microservices, preferably using FastAPI. Strong understanding of machine learning and deep learni

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