Description

Key Responsibilities:

Implement ML models (Decision Trees, Random Forest, XGBoost, etc.)
Develop & optimize structured data models for predictive analytics
Apply statistical techniques & Exploratory Data Analysis (EDA)
Build & deploy Python REST APIs (Flask/FastAPI)
Work with LLMs (RAG, Few-Shot Prompting, Supervised Fine-Tuning)
Design MLOps architectures for automation & scalability
Deploy ML workloads on AWS/GCP & integrate CI/CD pipelines


Required Skills:
5+ years of hands-on ML experience
Proficiency in Python, ML frameworks (Scikit-Learn, PyTorch, TensorFlow, Keras)
Experience in cloud computing (AWS/GCP) & containerization (Docker, Kubernetes)
Understanding of LLM techniques (RAG, Fine-Tuning, Prompt Engineering)
 

Key Skills
Education

Any Graduate

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