Hiring Generative AI Engineer

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. This has to be complimented with hands-on experience integrating OpenAI's GPT models with such Python applications