The role is an intersection of AIML, Generative AI and Technology. You will be required to develop key
integrations with RAG, develop modules and solutions for Agentic AI Platform as well as train/fine-tune
models on proprietary data. While the role would be a combination of AI and Tech - it is highly weighed
toward AI. You will be involved in developing innovative solutions to complex business problems.
You will collaborate closely with cross-functional teams to extract actionable insights from large and diverse datasets, enabling the company to make informed strategic decisions.
- Develop and implement advanced statistical, ML/AI, and LLM models to solve complex business problems and optimize performance.
- Fine-tune and train domain-specific LLMs, including multi-modal (text, speech, vision, image) models.
- Design and implement RAG systems and GenAI architectures (e.g., Knowledge Graphs, modular agent architectures) for enhanced agent outcomes.
- Finetune, Train & Deploy LLM Models, Vision Models, Voice Models
- Should be able to manage Model Ops & Deployment
- Develop Modules for Agents like Guardrails, Caching, Model Compression, Evaluations etc.
- Read, interpret, and implement complex academic research, adapting it into scalable, enterprise-ready AI systems.
- Support in developing end-to-end data science pipelines: data collection, cleaning, feature engineering, model development, validation, deployment.
- Apply MLOps/LLMOps practices for model lifecycle management and continuous improvement.
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