Role: Machine Learning Developer
Location: INDIA-PUNE (Work from office)
About The Role
The ML Developer will design, build, and maintain machine learning models and data pipelines powering core business use cases. The role is hands-on with Python for model development, feature engineering, and pipeline automation, leveraging Azure ML, and Azure DevOps. Success means robust, production-grade models with proven business impact, traceable lineage, and operational excellence at scale.
Responsibilities
- Feature Engineering & Model Development o Translate model prototypes from Data Scientists into Azure ML production pipelines, o including data ingestion, training, inference, and retraining.
- Build and iterate on ML models (forecasting/classification/regression) using modern ML
- frameworks (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow).
- Develop robust feature pipelines (deterministic code, modular definitions, reusability)
- using Pandas/PySpark and orchestrate in AML Pipelines Jobs.
- Design experiments with proper sampling, train-test splits, cross-validation, and metrics
- selection (e.g., RMSE, AUC, MAPE).
- Implement model selection, champion/challenger promotion, and versioning strategies.
- Document experiment results for reproducibility and regulatory compliance.
- Model Operationalization & Monitoring
- Productionize models as batch or real-time endpoints via Azure ML.
- Implement model validation gates (drift/shift, prediction distribution checks, champion o vs. challenger results).
- Set up model monitoring dashboards for latency, prediction freshness, data drift, and o feature importance tracking.
- Integrate model deployment/test harnesses with Azure DevOps pipelines for CI/CD.
- Develop FastAPIs to invoke and consume ML models.
- Data Engineering & Quality o Profile, clean, and transform raw data from Snowflake, SQL, and third-party sources.
- Implement checks for data quality (nulls, schema validation, outlier handling, time o alignment, duplicate detection).
- Automate feature extraction and maintain feature store consistency.
Required Qualifications
- 5+ years developing data-focused solutions (3+ years in ML modelling and operations).
- Advanced proficiency in Python (pandas, NumPy, ML frameworks), SQL, and cloud data tools.
- Solid experience building production ML pipelines (Azure ML, Databricks, or equivalent).
- Understanding of model validation, drift detection, and online monitoring.
- Experience with feature stores, CI/CD (Azure DevOps), and API development (FastAPI/Flask).
- Bachelor's/Master's degree in Computer Science, Statistics, Information Technology or related field.
- Certification in Azure Data or ML Engineer Associate is a plus.
