Position: DevOps
Company: Grid Dynamics
Category: DevOps
Experience required: 3y
English level: intermediate

**Project Description:**

 - Continuously analyze thousands of signals
IoT sensors generate a large number of signals, which can be challenging to monitor, analyze, and react to. Our platform for Industry 4.0 analytics can monitor thousands of signals continuously, learning normal patterns and detecting anomalous behavior.

- Detect anomalies early, prevent propagation
High latency in anomaly detection can result in financial losses, major outages, and liabilities. At the same time, instant anomaly detection is challenging because of noises and outliers that lead to false positives. Our anomaly detection models are designed to optimize the trade-off between detection latency and accuracy using variable time windows and analysis of historical patterns.

 - Detect cross-metrics patterns
IoT metrics are often collected from complex environments that have multiple interrelated components. In such environments, the analysis of individual metrics can be inefficient because the presence or absence of anomalies in individual signals does not fully characterize the status of the entire environment. Our platform uses topology-aware deep learning models that account for dependencies among sensors and learn complex patterns that involve multiple metrics.

- Investigate issues using advanced tools
Anomaly detection is only part of a complex process that includes issue triaging, root cause analysis, troubleshooting, and feedback-based system tuning. Our anomaly detection models are engineered from the ground up to provide advanced insights that help to investigate issues: anomaly timeframes, severity scores, and correlated metrics. Our solutions also include advanced dashboards for visualizing these insights and performing root cause analysis.

**Details on tech stack**: AWS, Greengrass, IoT, RasberyPI

**The main task of the candidate**: Build IoT PipeLine with AWS Greengrass 

If you are interested in this project, please leave your CV and I will write you :)