AI Scientist -1

Navi is hiring for the role of AI Scientist -1! Responsibilities of the Candidate: Develop and implement Generative AI (GenAI) based solutions tailored to create business impact and enhance customer experience at Navi. This involves understanding specific business needs and creating innovative AI-driven strategies. Collaborate extensively with cross-functional teams, including product managers and software engineers, to conceptualize, solutionize, and deploy AI solutions. Ensure seamless integration of AI solutions into existing workflows and platforms. Design, test, and refine AI prompts by leveraging advanced prompt engineering techniques. This includes researching and identifying the most effective ways to frame problems and elicit accurate responses from AI systems. Continuously define and monitor key quality metrics (such as accuracy, relevance, and completeness) and latency metrics (such as response time and processing speed) of AI deployments. Use insights gathered to make iterative improvements to models and prompts, ensuring they meet or exceed industry benchmarks. Stay informed about the latest advancements in GenAI, machine learning, and related technologies, applying innovative techniques to enhance Navi's AI capabilities. Requirements: Upto 2 Years of experience Bachelor's or Master's degree in Engineering, Computer Science, or a closely related discipline from a recognized institution. Superior verbal and written communication skills are essential, enabling the creation of detailed, contextually accurate AI and solutions. Demonstrated ability in high-level critical thinking and problem-solving, particularly in evaluating AI-generated outputs and iterating prompts to enhance the performance and reliability of AI solutions. Proficiency in programming, preferably in Python. Exceptional analytical skills, with the ability to detect patterns, recognise biases, and ensure the generation of high-quality AI outputs. Bonus: An in-depth understanding of the operational principles and mechanisms behind large language models (LLMs), including experience with optimizing and customizing such models for specific business use cases.