Senior AI/ML Engineer - R01558791

Key Responsibilities

Statistical Analysis & Experimentation

• Perform hypothesis testing using T-Test, Z-Test, and other statistical methods
• Apply regression techniques (linear and logistic) for predictive modeling
• Conduct classification modeling using Decision Trees and SVM
• Use probabilistic graph models for advanced analytical insights

Machine Learning Model Development

• Build and deploy ML models using frameworks like TensorFlow, PyTorch, Scikit-learn, Keras, MXNet, and CNTK
• Perform forecasting using ARIMA, ARIMAX, and Exponential Smoothing techniques
• Apply advanced distance metrics such as Euclidean, Manhattan, and Hamming distance in model design

Data Engineering & Processing

• Develop scalable data pipelines using Python and PySpark
• Perform statistical computing using SAS, SPSS, and R/R Studio
• Ensure high-quality data processing and transformation for analytics and ML workflows

Data Quality & Monitoring

• Implement data validation frameworks using Great Expectations
• Monitor model performance and data drift using Evidently AI
• Ensure reliability, consistency, and accuracy of data pipelines

Agentic AI & Advanced AI Systems

• Contribute to the development of Agentic AI systems for autonomous decision-making
• Work with orchestration and deployment tools such as Kubeflow and BentoML
• Support end-to-end ML lifecycle management including deployment and monitoring

Forecasting & Advanced Analytics

• Build time-series forecasting models for business and operational insights
• Apply advanced statistical and probabilistic techniques for decision support
• Translate analytical outputs into actionable insights for stakeholders

Collaboration & Problem Solving

• Work closely with data science and engineering teams to solve complex business problems
• Support cross-functional teams in adopting AI-driven solutions
• Communicate analytical findings clearly to technical and non-technical stakeholders