Senior ML Engineer (Data Platform)
3010 - Bangalore Office, India
INR 2800K-4000K (estimate) Senior-level Full Time
Tasks
- Build and deploy end to end ML systems in production
- Build and maintain MLOps pipelines including model versioning deployment monitoring and rollback
- Design build and optimize scalable batch and near real time data pipelines
- Develop and maintain data models
- Ensure data quality, observability, and reliability
- Implement Delta Lake and lakehouse architectures
- Integrate ML models into data platforms and downstream applications
- Mentor engineers and contribute to data and ML engineering best practices
- Own ML lifecycle feature engineering pipelines model training evaluation batch and real time inference monitoring and retraining
- Participate in architecture discussions for scalability performance and cost optimization
- Partner with product marketing sales and platform teams to translate business problems into scalable ML solutions
Perks/Benefits
- Employee assistance program
- Employee resource groups
- Employee wellness program
- Paid Holidays
- Paid time off
- Remote work stipend
- Tuition reimbursement
- Volunteering support
Skills/Tech-stack
AWS | Airflow | Amazon S3 | Batch inference | Data Modeling | Data Observability | Data Quality | Data Reliability | Databricks | Debugging | Delta Lake | Deployment | ELT | ETL | Feature Engineering | GenAI | LLM | Lakehouse | MLOps | Machine Learning | Model Evaluation | Model Training | Model versioning | Monitoring | PySpark | Python | Real Time | Real-time Inference | Retraining | Rollback | SQL
Education
N/A
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