Senior Machine Learning Engineer (Data & Audience Platform Team), Hyderabad
INR 2817K-3880K (estimate) Senior-level Full Time
Tasks
- Build feature pipelines with feature contracts and SLAs
- Build probabilistic identity resolution models
- Collaborate with product and data engineering on data contracts
- Configure governed natural language analytics with Databricks Genie
- Deploy and monitor batch and near real time inference
- Design production machine learning systems
- Detect data drift and monitor model health
- Develop lookalike and audience propensity models
- Implement MLOps model versioning and promotion
- Implement two tower retrieval and ranking models
- Leverage AI-assisted development workflows
- Measure incrementality with causal inference
- Mentor engineers through code reviews and design discussions
- Own feature engineering and model training
- Prototype agentic ML workflows
- Run offline and online experiments
- Use Snowflake Cortex for data discovery and SQL assistance
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AUC-ROC | Amazon Web Services | B testing | Bandits | Batch inference | Candidate Blocking | Causal Inference | Champion Challenger | Customer Analytics | Data Drift | Data Drift Detection | Data Quality | Data Quality Checks | Databricks | Delta Lake | Drift Detection | Embedding | Entity Resolution | Feature Engineering | Feature Store | Forecasting | Gradient boosting | Incrementality | Isotonic Regression | Lambda | Langchain | Langgraph | LightGBM | MLflow | Machine Learning | Model Monitoring | Model versioning | NDCG | Near Real Time Inference | Near-real-time | Neural ranking | NumPy | Optimization | Pandas | Precision-recall | Probability calibration | Propensity scoring | PySpark | Python | Quality checks | RAG | Ranking | Real-time Inference | Recommendations | Representation Learning | S3 | SQL | SageMaker | Snowflake | Two Tower Retrieval | Two-Tower | Unity Catalog | Uplift Modeling | Web Services | Workflows DLT | XGBoost
Education
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