Description

You will design, develop, and deploy machine learning models and scalable architectures.

This role is on-site.

Responsibilities

• Implement ML models including Decision Trees, Random Forest, and XGBoost.
• Develop and optimize structured data models for predictive analytics using statistical techniques and EDA.
• Build and deploy Python REST APIs using Flask or FastAPI.
• Work with LLMs using RAG, Few-Shot Prompting, and Supervised Fine-Tuning.
• Design MLOps architectures for automation and deploy workloads on AWS or GCP using CI/CD pipelines.

Required Skills

• 5+ years of hands-on machine learning experience.
• Proficiency in Python.
• Experience with ML frameworks including Scikit-Learn, PyTorch, TensorFlow, and Keras.
• Experience with cloud computing on AWS or GCP.
• Experience with containerization using Docker and Kubernetes.
• Understanding of LLM techniques such as RAG, Fine-Tuning, and Prompt Engineering.
• Ability to deploy ML workloads and integrate CI/CD pipelines.

Key Skills

Education

Any Graduate