AI Researcher - Generative AI/Machine Learning

As an AI Researcher at our company, your role will involve designing, developing, and deploying advanced AI/ML and Generative AI models. You will work on the end-to-end AI model lifecycle from research, experimentation, validation, deployment, and monitoring. Collaborating with engineering and business teams, you will solve real-world financial services problems. Additionally, you will be responsible for publishing and contributing to research papers in AI/ML/GenAI domains and optimizing AI models for production-grade performance, scalability, and reliability. Key Responsibilities: - Design, develop, and deploy advanced AI/ML and Generative AI models. - Work on end-to-end AI model lifecycle from research, experimentation, validation, deployment, and monitoring. - Develop scalable AI solutions using MLOps best practices. - Research and implement Transformer-based architectures and Deep Learning models. - Build Explainable AI (XAI) frameworks for transparent and interpretable AI systems. - Collaborate with engineering and business teams to solve real-world financial services problems. - Publish and contribute to research papers in AI/ML/GenAI domains. - Optimize AI models for production-grade performance, scalability, and reliability. Qualifications Required: - M.Tech or PhD is mandatory. - 7-10 years of relevant experience in AI/ML/GenAI. - Minimum 2-3 research publications in AI / GenAI / ML / Data Science. - Strong understanding of Transformer Architecture. - Hands-on expertise in MLOps and model deployment. - Strong knowledge of Deep Learning and Reinforcement Learning. - Experience with Explainable AI (XAI). - Ability to work across both research and production engineering environments. In addition to the above, if you have experience in Banking, Financial Services, Credit Risk, or FinTech domain, exposure to cloud platforms, scalable AI infrastructure, strong programming skills in Python and AI/ML frameworks, experience with data pipelines, APIs, and enterprise AI integration, it would be a plus. Please note that the key technologies you will be working with include Python, TensorFlow/PyTorch, MLOps, Transformer Models, LLMs/Generative AI, Deep Learning, Reinforcement Learning, Explainable AI (XAI), and Cloud Platforms. (ref:hirist.tech) As an AI Researcher at our company, your role will involve designing, developing, and deploying advanced AI/ML and Generative AI models. You will work on the end-to-end AI model lifecycle from research, experimentation, validation, deployment, and monitoring. Collaborating with engineering and business teams, you will solve real-world financial services problems. Additionally, you will be responsible for publishing and contributing to research papers in AI/ML/GenAI domains and optimizing AI models for production-grade performance, scalability, and reliability. Key Responsibilities: - Design, develop, and deploy advanced AI/ML and Generative AI models. - Work on end-to-end AI model lifecycle from research, experimentation, validation, deployment, and monitoring. - Develop scalable AI solutions using MLOps best practices. - Research and implement Transformer-based architectures and Deep Learning models. - Build Explainable AI (XAI) frameworks for transparent and interpretable AI systems. - Collaborate with engineering and business teams to solve real-world financial services problems. - Publish and contribute to research papers in AI/ML/GenAI domains. - Optimize AI models for production-grade performance, scalability, and reliability. Qualifications Required: - M.Tech or PhD is mandatory. - 7-10 years of relevant experience in AI/ML/GenAI. - Minimum 2-3 research publications in AI / GenAI / ML / Data Science. - Strong understanding of Transformer Architecture. - Hands-on expertise in MLOps and model deployment. - Strong knowledge of Deep Learning and Reinforcement Learning. - Experience with Explainable AI (XAI). - Ability to work across both research and production engineering environments. In addition to the above, if you have experience in Banking, Financial Services, Credit Risk, or FinTech domain, exposure to cloud platforms, scalable AI infrastructure, strong programming skills in Python and AI/ML frameworks, experience with data pipelines, APIs, and enterprise AI integration, it would be a plus. Please note that the key technologies you will be working with include Python, TensorFlow/PyTorch, MLOps, Transformer Models, LLMs/Generative AI, Deep Learning, Reinforcement Learning, Explainable AI (XAI), and Cloud Platforms. (ref:hirist.tech)