AI & Gen AI - Products & Tools E1

Role & responsibilities

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, Langraph 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.

Preferred candidate profile