ML Engineer

Job Summary:
We are seeking a Machine Learning Engineer to develop and operationalize scalable ML models and feature engineering pipelines within ecosystem. This role focuses on production-grade ML systems, MLOps, and continuous model optimization.

Key Responsibilities:
Design, develop, deploy, and optimize machine learning solutions.
Build scalable feature engineering pipelines and ML workflows.
Collaborate with data scientists, architects, and engineers on ML solutions.
Develop and maintain model training, inference, and monitoring pipelines.
Implement MLOps practices including model versioning and automated retraining.
Conduct model evaluation, optimization, and monitoring activities.
Troubleshoot issues across the ML stack and improve system reliability.
Support production deployments and operational activities.

Required Skills & Experience:
4+ years of professional ML Engineering experience.
Strong expertise in Python, PySpark, SQL, Scala, and Spark.
Hands-on experience with ML frameworks including Scikit-learn, TensorFlow, PyTorch, XGBoost, and MLflow.
Experience with Databricks, Delta Lake, and feature engineering tools.
Knowledge of REST APIs using FastAPI or Flask.
Familiarity with Docker, Kubernetes, and cloud ML platforms.
Experience with monitoring tools such as Grafana and Azure Monitor.

Preferred Qualifications:
Retail industry experience preferred.
Knowledge of A/B testing and causal inference is a plus.
Strong Agile delivery and communication skills.