You Are:
AI Azure Engineer
Key Responsibilities:
- Understand and analyse stress workloads:
· Monitor and interpret telemetry data related to memory usage, power consumption, and system performance.
· Identify stress thresholds and performance bottlenecks.
- Generate and analyse failure signatures:
· Recreate failure scenarios under different stress conditions.
· Design and implement processes for capturing and categorizing failure signatures.
- Correlate telemetry data with failure signatures:
· Build logic to link anomalies in telemetry data to corresponding system failures.
· Use statistical and ML techniques to establish root cause relationships.
AI & Analytics
- Experience running AI analytics on telemetry and failure data.
- Proficiency in Azure AI Studio and Azure Machine Learning tools.
- Ability to use Copilot-style prompting to:
· Ingest and pre-process telemetry data.
· Run exploratory data analysis.
· Build and deploy ML models to predict failures or performance issues.
Problem Solving & Solutioning
- Strong ability to:
· Understand abstract or ambiguous problem statements.
· Provide solutions using Azure AI .
Azure AI Studio & Copilot Prompts
- Ability to create and use prompts to:
· Analyse telemetry dataset and identify memory and power-related anomalies.
· Generate failure signatures based on historical performance degradation.
· Suggest optimization strategies.
Statistical Knowledge
- Knowledge of time-series data, anomaly detection, and predictive modelling.
- Descriptive analysis
- Inferential Analysis - Hypothesis testing (T Test, ANOVA), Confidence Interval, Chi Sq test
- Predictive Analysis - Regression Analysis, Time series forecasting
- Annamolly detection
- Decision Trees, What if Analysis , Optimization Algorithms
Skillset Required
- Programming language: Python - NumPy & Pandas
- ML Framework: TensorFlow, PyTorch, Scikit-learn
- Database Management: KQL, SQL (any)
- Data modelling:
- Strong experience in data modelling, especially in predictive and behavioral analytics.
- Proficiency in collecting, parsing and analyzing telemetry logs.
- Familiarity with cloud data pipelines (Azure)
- Experience with Machine Learning framework and data science toolkits.
- Azure Data Engineering:
- Migrating the data from JSON to Azure Data Factory (Kustos)
- Knowledge in querying the telemetry data in Kustos.