Applied AI & ML Lead [Multiple Positions Available]
Tasks
- Analyze data trends and model outputs
- Apply community detection and label propagation
- Apply graph neural networks for fraud detection
- Build payment transaction graphs
- Collaborate on model deployment
- Compute graph connectivity metrics
- Conduct exploratory data analysis
- Create risk scores with temporal features
- Deploy real time models for low latency detection
- Design machine learning models for fraud detection
- Develop distributed feature engineering pipelines
- Engineer graph based features and embeddings
- Ensure model interpretability and compliance
- Lead model development lifecycle
- Track model performance metrics
Perks/Benefits
- Backup childcare
- Financial coaching
- Health insurance
- Mental health support
- Onsite wellness centers
- Retirement savings plan
- Tuition reimbursement
Skills/Tech-stack
Airflow | Apache Beam | Attention Networks | BigQuery | CI/CD | Dask | Decision Trees | Docker | Graph Attention | Graph Attention Networks | Graph Neural Networks | GraphSAGE | KMeans | Kafka | Keras | Kubernetes | LIME | LightGBM | Machine Learning | Matplotlib | Metapath2Vec | NetworkX | Neural Networks | Node2vec | Plotly | PySpark | PyTorch | PyTorch Geometric | Python | SHAP | SQL | Scikit-learn | Seaborn | Series analysis | Snowflake | Supervised Learning | TensorFlow | Time Series | Time Series Analysis | Unsupervised Learning | XGBoost
Regions
Countries
States
Cities
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