ML/AI Engineer II-2
Tasks
- Build and optimize time series forecasting frameworks
- Collaborate with stakeholders to translate domain challenges into analytical solutions
- Create reusable model components and evaluation workflows
- Develop predictive and prescriptive models
- Ensure model governance explainability and responsible AI
- Integrate generative AI and multi agent systems with traditional ML
- Lead design and development of AI and analytics solutions
- Monitor model performance and improve production models
- Perform exploratory data analysis and feature engineering
- Stay current with advances in machine learning and agentic AI
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | ARIMA | Agent systems | Anomaly Detection | Autogen | B testing | Bayesian Inference | Cause analysis | Clustering | Counterfactuals | CrewAI | Cross-validation | Data Analysis | Deep learning | Drift Detection | ETS | Ensemble learning | Error Decomposition | Exploratory Data Analysis | Fairness | Feature Engineering | GRU | Generative AI | Hyperparameter Tuning | LSTM | Langgraph | Language Processing | Machine Learning | Model Benchmarking | Model Explainability | Model Governance | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Partial Dependence | Probabilistic Modeling | Prophet | Regression | Responsible AI | Root Cause Analysis | Root cause | SARIMA | SHAP | Series forecasting | State Space Models | State-Space | Supervised Learning | Time Series | Time Series Forecasting | Transparency | Unsupervised Learning | VAR
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