Description

You will lead the architecture, design, and deployment of machine learning solutions to drive business value.

Responsibilities

• Architect and design end-to-end machine learning solutions from conception to production.
• Deploy machine learning models that deliver measurable organizational value.
• Implement advanced generative AI workflows including RAG and agentic systems.
• Integrate MLOps practices and cloud security standards into the ML lifecycle.

Required Skills

• 10+ years of experience in machine learning architecture and deployment.
• Deep expertise in econometric and statistical methods including Linear/Logistic Regression, GLM, Survival Analysis, and Time Series Analysis.
• Proficiency in statistical techniques such as PCA, Factor Analysis, Clustering, and Discriminant Analysis.
• Hands-on experience with ML algorithms like Random Forest, SVM, GBM, and XGBoost.
• Expertise in Deep Learning, specifically RNNs, CNNs, and Transformer architectures for NLP and Computer Vision.
• Practical implementation of Generative AI techniques including RAG, Agentic Workflows, Graph RAG, and Model Tuning.
• Extensive experience with MLOps and Cloud Security.
• Strong foundation in sampling techniques, CART, and CHAID.

Key Skills

Education

Any Gradute