Hypothesis Testing T-Test Z-Test Regression (Linear Logistic) Python/PySpark SAS/SPSS Statistical analysis and computing Probabilistic Graph Models Great Expectation Evidently AI Forecasting (Exponential Smoothing ARIMA ARIMAX) Tools(KubeFlow BentoML) Classification (Decision Trees SVM) ML Frameworks (TensorFlow PyTorch Sci-Kit Learn CNTK Keras MXNet) Distance (Hamming Distance Euclidean Distance Manhattan Distance) R/ R Studio
Job requirements
Key Responsibilities - Develop and optimize machine learning models for various applications. - Implement AI algorithms including deep learning neural networks and natural language processing (NLP). - Design and maintain data pipelines for model training and deployment. - Collaborate with cross-functional teams to integrate AI solutions into products. - Conduct research on emerging AI technologies and best practices. - Ensure scalability reliability and efficiency of AI models in production environments. - Troubleshoot and improve existing AI/ML systems. Required Skills & Qualifications - Experience: 3-8 years in AI/ML development. - Technical Skills: Proficiency in Python TensorFlow PyTorch and other ML frameworks. - Data Handling: Strong knowledge of data preprocessing feature engineering and model evaluation. - Cloud & Deployment: Experience with cloud platforms (AWS Azure GCP) and containerization (Docker Kubernetes). - Problem-Solving: Ability to analyze complex problems and develop AI-driven solutions.
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