Staff Applied ML Engineer
Tasks
- Build machine learning models for anomaly detection
- Build manufacturing intelligence systems
- Convert model outputs into operational logic
- Deploy model services and production APIs
- Design data pipelines for operational use
- Develop feature generation and inference workflows
- Identify process drift and fault patterns
- Ingest plant telemetry and event data
- Quantify operational risk before failures
- Reconstruct equipment and process behavior
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Airflow | Anomaly Detection | Apache Spark | DBT | Data Pipelines | FastAPI | Fault classification | Feature Engineering | Flask | Forecasting | Industrial IoT | Machine Learning | NumPy | Pandas | Predictive Maintenance | Process monitoring | PyTorch | Python | Quality Prediction | SQL | SciPy | Scikit-learn | Sensor data | Series analysis | StatsModels | TensorFlow | Time Series | Time Series Analysis | XGBoost
Education
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