ML/AI Engineer II-2
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The role
Lead design and delivery of secure, scalable AI/ML solutions spanning classical ML, time-series forecasting, deep learning, and emerging agent-based architectures.
Develop predictive and prescriptive models using supervised, unsupervised, Bayesian, and ensemble methods for financial and operational use cases.
Build and optimize time-series forecasting frameworks (ARIMA/SARIMA, ETS, Prophet, VAR) and LSTM/GRU-based forecasting pipelines.
Integrate Generative AI and multi-agent systems with traditional ML to enable intelligent decision support and automated domain tasks.
Ensure governance and explainability with SHAP, counterfactuals, drift detection, and responsible AI practices; monitor production models and conduct A/B experiments.
Collaborate with business stakeholders and data engineering to translate challenges into measurable analytics with ROI, while staying current with advances in AI.
Develop predictive and prescriptive models using supervised, unsupervised, Bayesian, and ensemble methods for financial and operational use cases.
Build and optimize time-series forecasting frameworks (ARIMA/SARIMA, ETS, Prophet, VAR) and LSTM/GRU-based forecasting pipelines.
Integrate Generative AI and multi-agent systems with traditional ML to enable intelligent decision support and automated domain tasks.
Ensure governance and explainability with SHAP, counterfactuals, drift detection, and responsible AI practices; monitor production models and conduct A/B experiments.
Collaborate with business stakeholders and data engineering to translate challenges into measurable analytics with ROI, while staying current with advances in AI.
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