Key Responsibilities:
- Key Responsibilities
- Machine Learning Engineering
- Develop train evaluate and deploy machine learning models at scale
- Implement end to end ML pipelines from data ingestion to model serving
- Work on model optimization validation and performance monitoring
- Apply best practices for feature engineering and model lifecycle management
- MLOps Deployment
- Build and maintain MLOps pipelines for CI CD CT Continuous Training
- Automate model deployment versioning and monitoring
- Implement experiment tracking and model registry MLflow preferred
- Ensure model reproducibility scalability and governance
- Python OOPs Development
- Develop modular reusable and scalable code using object oriented Python
- Build robust backend services and ML utilities
- Write clean testable and well documented code
- Databricks
- Develop and optimize workflows on Azure Databricks
- Work with PySpark for data processing and feature engineering
- Manage notebooks jobs clusters and Delta Lake pipelines
- Optimize Spark jobs for performance and cost
- Azure Cloud
- Work with Azure services like Azure ML Data Factory Blob Storage ADLS Key Vault
- Deploy models and pipelines using Azure DevOps CI CD pipelines
- Implement secure scalable and cost efficient cloud architectures
- Data Engineering Integration
- Build and maintain data pipelines for ML workflows
- Integrate models with APIs and downstream applications
- Work with large datasets structured unstructured
Technical Requirements:
- Required Skills Qualifications
- Core Skills
- 3 5 years of experience in Machine Learning MLOps
- Strong proficiency in Python with OOP concepts mandatory
- Hands on experience with Databricks PySpark
- Solid experience with Azure cloud ecosystem
- Technical Skills
- Experience with ML frameworks Scikit learn TensorFlow PyTorch
- Hands on with MLflow experiment tracking model registry
- Knowledge of CI CD tools Azure DevOps Jenkins GitHub Actions
- Strong understanding of data structures algorithms and system design basics
- Experience with REST APIs and microservices
- Preferred Skills
- Exposure to feature stores and model monitoring tools
- Knowledge of Docker Kubernetes
- Familiarity with Delta Lake data lakes and warehouse architectures
- Experience with streaming Kafka Event Hub
- Understanding of data governance and security best practices
Preferred Skills:
Technology->AI-Data science->Databricks Machine Learning,Technology->AI-Data science->PYTHON,Technology->Data Engineering->Databricks,Technology->Cloud Platform->Azure Networking Services->Azure NAT Gateway
