Data Scientist AI/ML Developer

As a Data Scientist AI/ML Developer, you will be responsible for various key tasks related to data collection, analysis, model development, and implementation of advanced technologies. You should have a strong understanding of data science methodologies and experience in working with machine learning models. This position is suitable for freshers as well as candidates with up to 5 years of experience. Your primary responsibilities will include gathering, cleaning, and analyzing large datasets for diverse applications. You will also be involved in building, training, and evaluating machine learning and deep learning models for tasks related to computer vision, natural language processing (NLP), and generative AI. You will utilize OpenCV to create solutions for image classification, object detection, facial recognition, and other vision-based tasks. Additionally, you will develop and fine-tune Generative Adversarial Networks (GANs) for synthetic data generation and image manipulation. Collaboration with cross-functional teams is essential in this role, as you will work closely with data engineers, software developers, and business analysts to integrate data-driven insights into production environments. Staying updated with the latest developments in AI, data science, and generative AI is crucial, and you should be able to apply best practices to projects effectively. Ensuring that machine learning models and data pipelines are scalable, efficient, and ready for production deployment is also a key part of your responsibilities. In terms of required skills, you should have strong proficiency in computer vision techniques using OpenCV, hands-on experience with Generative Adversarial Networks (GANs), and familiarity with LangChain, GPT models, and other generative AI frameworks. Proficiency in Python and relevant ML libraries such as TensorFlow and PyTorch is essential. Expertise in data preprocessing, feature engineering, and working with large datasets is also required. Preferred skills include experience in Natural Language Processing (NLP), model deployment using cloud services and containerization, familiarity with transformer architectures, and knowledge of big data technologies. Additionally, possessing soft skills such as strong problem-solving abilities, effective communication, and a continuous learning mindset will be advantageous in this role.,