Key Responsibilities :

- Develop end-to-end scalable, optimized enterprise AI solutions.

- Engage in prompt engineering and fine-tuning of AI/ML models, including Generative AI (GenAI) and Large Language Models (LLMs), as well as building and managing multi-agent systems.

- Implement practical hands-on fine-tuning, transfer learning, and optimization of Transformer architecture-based deep learning models.

Technical Skills :

- Proficient in Agentic AI, GenAI, and LLM technologies, with experience in NLP tools such as Word2Vec, NLTK, SpaCy, BERT, GloVe, Autogen, Semantic Kernel, Lang chain, and Langraph.

- Hands on development experience with development of AI agents.

- Familiarity with either of cloud platforms like Azure ,AWS or Google Cloud

- Strong programming skills in Python, with experience in frameworks such as Flask for lightweight applications and FastAPI for API development.

- Proficient in using Docker for container deployment and deploying ML models on Kubernetes clusters.

- Experience with NoSQL, SQL, and vector databases.

- Strong understanding of statistical methods and experimental design.

- Familiarity with MLOps practices for continuous integration and continuous deployment (CI/CD) in machine learning.

- Experience in prompt fine tuning and performance optimization

- Experience using Python Memory management tools like Scalene or Filprofiler or similar

- Experience in any of the Frameworks like Langchain, Langgraph etc.

- Familiarity of having worked on packages such as Python-pptx, pymupdf to read PPTX or pdf documents.