Machine Learning Engineer - Python/AWS (2-6 yrs)

Summary :

As a ML Engineer, you will be responsible for data pre-processing (using python/pyspark dataframe), feature engineering, model deployment, model management and model monitoring of machine learning application in production environments.

Educational Qualification : Bachelors' or Master's degree in Computer Science, Engineering, Data Science or a related fields

Key Responsibilities :

- Model deployment and monitoring using AWS Sagemaker

- ML use case deployment in cloud - AWS Sagemaker

- Data pre-processing, feature engineering using python/pyspark

- Implement best practices for model versioning, testing and validation

- Ensure scalability and reliability of ML infrastructure

- Troubleshoot and resolve issues related to model deployment and performance

- Develop and maintain documentation for ML operations and processes

Requirements :

- Experience in deploying and managing machine learning models in productions

- Strong programming skills in python, pyspark and familiarity with ML frameworks

- Experience with AWS cloud services (e.g. Sagemaker, Lambda, EMR etc.)

- Knowledge of ML algorithm (e.g. XGBoost, Decision Tree, Random Forest, Deep Learning etc.)

- Knowledge of CI/CD tools

- Strong problem-solving skills and ability to work in a fast-paced, collaborative environment

- Excellent communication skills and ability to work with cross-functional teams