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Position Overview We are seeking a motivated and talented AI Engineer at a fresher level to join our dynamic team. This role offers an excellent opportunity for recent graduates or early-career professionals to work with cutting-edge artificial intelligence technologies, focusing on language models, machine learning, and advanced AI techniques. Key Responsibilities · Design, develop, and implement AI solutions using state-of-the-art language models and machine learning techniques · Fine-tune pre-trained language models for specific use cases and domains · Implement and optimize Retrieval-Augmented Generation (RAG) systems for enhanced AI performance · Work with Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication frameworks · Develop and deploy machine learning models in local environments · Collaborate with cross-functional teams to integrate AI solutions into existing systems · Conduct experiments and analyze results to improve model performance · Stay updated with the latest developments in AI research and implement best practices · Document technical processes and maintain code quality standards Required Qualifications  Technical Skills · Programming Languages: Proficiency in Python (mandatory) · Machine Learning Frameworks: Hands-on experience with PyTorch, TensorFlow, ONNX, TensorRT, and related ML libraries · Language Models: Strong understanding of transformer architectures, fine-tuning techniques, and language model optimization · AI Techniques: Knowledge of RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol), and A2A (Agent-to-Agent) frameworks · Statistics: Solid foundation in statistical concepts and their application in machine learning · Local Model Deployment: Ability to set up and run ML models in local environments Core Competencies · Understanding of deep learning fundamentals and neural network architectures · Experience with model training, validation, and evaluation processes · Familiarity with data preprocessing and feature engineering techniques · Knowledge of version control systems (Git) and collaborative development practices · Problem-solving mindset with attention to detail Additional Technical Skills · Programming Languages: Experience with additional languages such as Java, C++, JavaScript, or Go · Specialized Tools: Experience with MATLAB and R for statistical computing and data analysis · NLP Expertise: Background in Natural Language Processing, including text preprocessing, sentiment analysis, named entity recognition, or language understanding tasks · Computer Vision: Knowledge of computer vision techniques, image processing, or vision-language models · Cloud Platforms: Familiarity with AWS, Google Cloud, or Azure ML services · MLOps: Understanding of ML pipeline development and deployment practices