Posted on: 21/02/2026
Description :
Verdantis (Ultria Software Pvt Ltd) is the only player to offer end-to-end automated, multilingual Master Data Management (MDM) and Master Data Governance (MDG) solutions for domains such as Material (or Item), Purchased Part and Product. Our Artificial Intelligence (AI) driven automated solutions are used by more than 80 of the Fortune 500 to leverage internal resources to manage their master data better and help their business turn out a better bottom-line performance.
Experience :
- Prompt Engineering : Design and optimize prompts to guide LLM outputs effectively, ensuring high-quality and contextually appropriate responses in various applications, including chatbots, virtual assistants, and content generation tools.
- Model Deployment and Integration : Work on the deployment of LLMs in production environments, ensuring scalability, reliability, and efficiency. Collaborate with software engineers to integrate models into existing platforms.
- Performance Monitoring and Improvement : Continuously monitor the performance of deployed models and iterate on them to improve accuracy, speed, and relevance of outputs.
- Data Management : Collaborate with data scientists and data engineers to manage, preprocess, and curate large datasets for training and evaluation of models.
- Research and Innovation : Stay updated with the latest advancements in AI, machine learning, and natural language processing. Propose and implement innovative solutions to improve existing systems or develop new AI capabilities.
- Collaboration : Work closely with cross-functional teams, including product managers, software developers, and UX/UI designers, to deliver AI-driven features and products.
- Documentation and Reporting : Maintain comprehensive documentation of models, algorithms, and system designs. Report progress and findings to stakeholders in a clear and actionable manner.
Technical Expertise :
- Proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch).
- Strong understanding of NLP techniques and frameworks.
- Experience with transformer models (e.g., GPT, BERT) and fine-tuning them for specific tasks.
- Hands-on experience with prompt engineering and model optimization.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) for AI model deployment.
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