Description

You will design, develop, and deploy machine learning models to solve complex business problems using multilayered datasets.

This role is hybrid.

Responsibilities

• Experiment with various models, evaluate performance, and conduct model selection.
• Perform data cleaning, feature engineering, and feature selection.
• Implement data and model training pipelines on AWS using SageMaker and Lambda functions.
• Document model architectures and technical solutions.
• Collaborate with platform engineers, data engineers, and software developers to meet business requirements.

Required Skills

• 3+ years of experience with Python, SQL, and Statistics.
• Deep learning experience using PyTorch or TensorFlow.
• Proficiency in advanced mathematics, including calculus, linear algebra, functional analysis, and Bayesian statistics.
• Experience with time series forecasting using Prophet or Elastin.
• Practical knowledge of predictive modeling for classification, clustering, and forecasting.
• Experience with object-oriented programming and the software development lifecycle.
• Exposure to deploying and monitoring models in production.
• Hands-on experience with version control systems like GitHub or CodeCommit.
• Exposure to Docker containerization.
• Technical experience developing and implementing cloud ML models on AWS.

Preferred Skills

• Experience with ensemble machine learning models.
• Familiarity with AWS services including ECS, Airflow, and Elasticsearch.
• Knowledge of DevOps practices and CI/CD pipelines for data solutions.

Key Skills

Education

Any Graduate