Senior Data & ML Engineer - 3.5 Yrs

Location : In-office

Years of Experience : 3.5+ years

What You'll Do

Architect and optimize batch + streaming data pipelines

Build ML-ready datasets & feature pipelines

Deploy & monitor ML models on AWS SageMaker / EC2 / Kubernetes

Implement full MLOps lifecycle (MLflow, CI / CD, retraining)

Ensure data quality, scalability, reliability

Mentor juniors & enforce code quality standards

Must Have Skills & Tech

Python (Pandas, NumPy, scikit-learn, PyTorch / TensorFlow, XGBoost / LightGBM)

SQL (advanced queries + optimization)

AWS (S3, EC2, Lambda, RDS, SageMaker)

PySpark, Kafka, MongoDB, Redis, Dask, Django

Docker + CI / CD, MLflow / SageMaker Model Registry

Production-level deployments (100M+ data points handled)

Good to Have

Airflow / Prefect / Dagster (orchestration)

Terraform / CloudFormation (infra as code)

Great Expectations / Soda (data observability)

Feature Stores, Vector Databases

Kubernetes, dbt, Golang