Job Overview
Category
Mathematical Science Occupations
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Job Description
Responsibilities
Design and optimize ML models for time series forecasting, anomaly detection, and computer vision (e.g., quality inspection)Apply advanced techniques such as LSTM, CNN, XGBoost, PCA, clustering, and Explainable AI (e.g., SHAP, LIME)Analyze structured and unstructured data from operational and sensor systemsDevelop and maintain robust ML pipelines for training, validation, deployment, and monitoringCollaborate with data engineers, solution architects, and IoT/Edge teams to ensure scalable integrationUse SQL and BI tools (e.g., Power BI) to prepare and visualize large datasetsWork with cloud platforms (e.g., AWS, Azure, GCP) for model deployment and MLOps lifecycle management Your Profile:
3+ years of hands-on experience developing and deploying ML models in production environmentsStrong Python skills and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch)Proficient in data preprocessing, feature engineering, and model validation techniquesFamiliarity with Explainable AI (XAI), data governance, and ethical AI principlesSolid SQL skills and experience with BI/dashboard tools such as Power BIExperience working with cloud-based ML services (e.g., SageMaker, Azure ML, Vertex AI)Strong communication skills and ability to explain technical results to both technical and business stakeholders Preffered Qualifications
Experience in Industry 4.0, manufacturing, or process automation projectsFamiliarity with real-time/streaming data platforms, time series databases, and tools like GrafanaUnderstanding of MLOps pipelines and tools for automated model management and deploymentExperience with orchestration tools such as Apache Airflow or dbt Application Process
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