Descrição do trabalho
- Key Responsibilities
- Translate business problems into Machine Learning problems , selecting appropriate modeling approaches and metrics.
- Prepare, split, and label datasets to support robust model training and evaluation.
- Define and compute features from multiple data sources.
- Design, execute, and evaluate experiments to assess model performance.
- Build, deploy, and maintain Machine Learning models in production using MLOps best practices .
- Define and monitor model performance and drift metrics , triggering model retraining when required.
- Collaborate closely with engineering and business stakeholders to ensure scalable and reliable solutions.
- Required Skills & Experience
- 2+ years of experience building and deploying Machine Learning models in production.
- Hands-on experience with MLOps setups , including CI / CD pipelines .
- Strong experience in time series–based event detection and classification .
- Solid background in classification models .
- Experience modeling geospatial time series data .
- Knowledge of 2D interpolation and extrapolation methods .
- Strong fundamentals in trigonometry and linear algebra (vector arithmetic).
- Proficiency in Python .
- Technical Stack
- Python and PySpark
- Spark
- Git
- Azure Pipelines
- Azure Databricks
- Azure-based cloud environments
