Data Scientist - Artificial Intelligence/Machine Learning

Job Description We are seeking an experienced AI ML Engineer/AI Data Scientist to join our team, with a strong background in Artificial Intelligence and Machine Learning. The ideal candidate will have 4 -7 years of experience in AI/ML and a proven track record of designing and deploying deep learning concepts to generate business value. Key Responsibilities Designing deep learning concepts and deploying machine learning solutions to generate business value Applying statistical and calculus concepts to drive business outcomes Working in the domains of Natural Language Processing (NLP) and/or Computer Vision (CV) Utilizing machine learning techniques like Random Forest, Support Vector Machine, and Gradient Boosting Machine Applying deep learning techniques across Recurrent Neural Networks, Convolutional Neural Networks, and Transformer Architectures Developing and deploying Generative AI techniques like RAG, Agentic Workflows, and Graph RAG Required Skills Experience : Experienced AI Scientist with 4 - 6 years of experience in AIML. Design : Designing deep learning concepts. Mathematics : Good in Statistical and Calculus concepts. Domains : Applied in the domains of Natural Language Processing (NLP) and / or Computer Vision (CV). Deployment : Generative AI and deploying Machine Learning (ML) solutions to generate business value. Statistical Methods : Solid theoretical and practical knowledge of some or most econometric/statistical methods like Linear Regression, Logistic regression, Generalized Linear Model, Survival Analysis, Sampling Techniques, Time Series Analysis, CART, CHAID, Clustering, Discriminant Analysis, Principal Component Analysis, Factor Analysis, Multidimensional Scaling etc. Machine Learning : Machine Learning techniques like Random Forest, Support Vector Machine, Gradient Boosting Machine, XGBoost etc. Deep Learning : Deep Learning techniques across Recurrent Neural Networks, Convolutional Neural Networks etc. and Transformer Architectures as applied in the domains of Natural Language Processing (NLP) and / or Computer Vision (CV) with a consistent track record of building and successfully deploying Machine Learning solutions with demonstrable value to the organization. Generative AI : Generative AI techniques like RAG, Agentic Workflows, Graph RAG, Model Tuning etc. (ref:hirist.tech) .