Location: Mumbai,None,None

At SiftHub, we are on a mission to make the life of sales and solutions teams more efficient and help them to focus on selling. SiftHub AI Sales Engineer empowers sales and pre-sales teams to improve win rates and close deals faster. SiftHub is an AI platform that acts as a central hub to collate and sift through all your content scattered across multiple repositories and tools such as Drive, Sharepoint, Confluence, CRM, Slack, product knowledge base. As a member of our team, you'll be at the forefront of this exciting technology revolution, working alongside some of the brightest minds in the industry to bring our platform to life. We're looking for individuals who are passionate about AI and its potential to drive real-world impact.Whether you're an AI expert or an aspiring one, SiftHub offers an environment that supports and challenges you, enabling your growth and success. Join us today and help us shape the future of AI for enterprises!ResponsibilitiesDesign and develop engaging, effective, and unambiguous NLP based AI systems, taking into account user intent, context, and desired resultsCollaborate with cross-functional teams, including product managers, UX/UI designers, and developers, to develop the best user experiencesConduct user research and evaluate user feedback in order to continuously finetune the modelsStay updated on industry trends, new technologies, and best practices in AI, NLP, and conversational designDevelop and keep up-to-date engineering documentation, including guidelines, best practices, and utilization examplesContribute to the process of quality assurance and DevOps by identifying and resolving issues to ensure model effectiveness and user satisfactionRequirementsBachelor’s or Master’s degree in Computer Science, Information Technology with a focus on language processing6+ years of experience in NLP and relevant projects with strong proficiency in PythonExperience in machine learning frameworks, libraries and large language models such as BERT, GPTUnderstanding of NLP techniques for text representation, semantic extraction techniques, data structures, and modelingExperience in implementing the products lifecycle - design, development, quality, deployment, maintenance
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