ML Engineer With Timeseries Data Experience
SoftStandard SolutionsContract
Required Skillset:
PythonPandasScikit-learnProphetanomaly detectionAWSPySparkTensorFlowNumPypredictive analyticsPyTorchtime-series modelsARIMA
Job Description
- Model Development: Design, build, train, and optimize ML/DL models for time-series forecasting, prediction, anomaly detection, and causal inference.
- Data Pipelines: Create robust data pipelines for collection, preprocessing, feature engineering, and labeling of large-scale time-series data.
- Scalable Systems: Architect and implement scalable AI/ML infrastructure and MLOps pipelines (CI/CD, monitoring) for production deployment.
- Collaboration: Work with data engineers, software developers, and domain experts to integrate AI solutions.
- Performance: Monitor, troubleshoot, and optimize model performance, ensuring robustness and real-world applicability.
- Languages & Frameworks: Good understanding of AWS Framework, Python (Pandas, NumPy), PyTorch, TensorFlow, Scikit-learn, PySpark.
- ML/DL Expertise: Strong grasp of time-series models (ARIMA, Prophet, Deep Learning), anomaly detection, and predictive analytics
- Data Handling: Experience with large datasets, feature engineering, and scalable data processing.
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