Senior Machine Learning Engineer
Tasks
- Build ML stack for production anomaly detection
- Design data pipelines and feature extraction
- Design experiments and define detection quality metrics
- Detect malicious behavioral patterns in API traffic
- Document findings and define ML roadmap
- Evaluate models using offline metrics
- Extract signals from API session text and structured data
- Monitor model performance drift and false positives
- Perform raw data exploration and feature engineering
- Serve models for real time detection
- Track experiments and manage model versioning
- Train and deploy anomaly detection models
- Use embeddings and LLM augmented approaches for signal enrichment
Perks/Benefits
Skills/Tech-stack
APIs | Anomaly Detection | Clustering | DVC | Data Exploration | Data Pipelines | Data Versioning | Drift monitoring | ETL | ETL Pipelines | Embeddings | Experiment tracking | Feature Engineering | Feature Stores | MLflow | Machine Learning | Model Serving | Model Training | NLP | Precision and Recall | Python | Statistical Methods | Streaming Data | Text Classification | Tokenization | Weights and Biases
Education
N/A
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