Data Scientist

1. Experience in Deep learning engineering (mostly on MLOps)
2. Strong NLP/LLM experience and processing text using LLM
3. Proficient in Pyspark/Databricks & Python programming.
4. Building backend applications (data processing etc) using Python and Deep learning frame works.
5. Deploying models and building APIS (FAST API, FLASK API)
6. Need to have experience working with GPU'S.
7. Working knowledge of Vector databases like 1) Milvus 2) azure cognitive search 3) quadrant etc
8. Experience in transformers and working with hugging face models like llama, Mixtral AI and embedding models etc.

Good to have:
1. Knowledge and experience in Kubernetes, docker etc
2. Cloud Experience working with VM'S and azure storage.
3. Sound data engineering experience