Job
Description
Youll create impact by: Apply Generative AI & NLP Techniques Utilize state-of-the-art Generative AI and NLP techniques to extract insights from large volumes of data with different modalities such as text, image, charts, graph, video, sound, 2D Drawing, 3D geometry, code & logs. Work on various Generative AI applications such as text generation, retrieval-augmented generation (RAG) systems, Q&A systems, and recommendation engines tailored for business and industrial contexts. Develop Innovative AI Applications with Agentic AI workflows Collaborate with cross-functional teams to create and enhance Agentic AI capabilities, including developing skill-based agents for specific tasks in industrial use cases. Fine-tune and benchmark Generative AI models using domain-specific datasets, focusing on performance improvement, reliability, and scalability. Implement and evaluate modality-specific encoder models (text, image, audio), optimizing them for specific industrial applications. Brainstorm and propose new application use cases for Generative AI in industrial setups, such as predictive maintenance, process optimization, and intelligent automation. Contribute to creating intellectual property (IP) and publish research findings in top-tier journals and conferences. Collaborate and Contribute in a fast-paced Environment Work effectively in an agile, dynamic team environment, delivering technical implementations with complex dependencies and requirements. Commitment to ethical AI practices, including bias mitigation, fairness, transparency, and data privacy. Strong collaboration skills to work with cross-functional teams and non-technical stakeholders. Youd describe yourself as: PhD/Masters/bachelors degree in computer science, Data Science, Artificial Intelligence, or a related field from a reputed institute. Experience: 2-5 years of experience in Generative AI, NLP, and related AI technologies, including model fine-tuning and evaluation. Technical Expertise: Solid understanding of Generative AI models and NLP techniques, including RAG systems, text generation, and embedding models. Exposure to Agentic AI concepts, agent development and frameworks Hands-on experience with Generative AI, machine learning tool, libraries and frameworks Knowledge of modality-specific encoder models (e.g., text, image, audio). Familiarity with data standardization and Knowledge Graphs (good to have). Analytical Mindset: Strong problem-solving skills with the ability to design and implement novel AI solutions. Dedication to continuous learning and staying updated on the latest Gen AI advancements. Excellent communication skills and the ability to work collaboratively in a team.
