Responsibilities:- Research, design, and implement machine learning models and algorithms to solve complex problems in diverse domains. - Utilize traditional ML techniques (e.g., regression, classification, clustering) and DL frameworks (e.g., TensorFlow, PyTorch) to build robust predictive models. - Develop and implement NLP solutions including sentiment analysis, text classification, entity recognition, and language generation. - Explore and implement state-of-the-art Generative AI techniques, including but not limited to GANs, Transformers, and language models. - Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. - Conduct thorough analysis and validation to ensure the quality, reliability, and scalability of models. - Fine-tune models through hyperparameter optimization and performance tuning. - Stay updated with the latest advancements in AI/ML research and methodologies. ### Requirements: - Proven experience (5+ years) in developing and deploying ML/DL models and NLP solutions. - Expertise in traditional ML algorithms and frameworks (e.g., SVM, Random Forest, scikit-learn). - Hands-on experience with DL frameworks such as TensorFlow, PyTorch, etc. - Proficiency in NLP libraries/tools (NLTK, spaCy, Transformers, etc.) and techniques. - Experience with Generative AI models and frameworks (e.g., GANs, BERT, GPT). - Strong programming skills in Python and familiarity with relevant libraries (numpy, pandas, etc.). - Solid understanding of software engineering principles and version control systems. - Ability to work independently and as part of a team, with excellent communication skills. - Demonstrated ability to innovate and solve complex problems effectively.
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