Description

Design, develop, and deploy AI/ML models and data science solutions on AWS.

This role is on-site.

Responsibilities

• Build end-to-end ML pipelines using AWS services including SageMaker, Lambda, EC2, and ECR.
• Perform advanced data analysis, feature engineering, and model optimization using Python.
• Work with large-scale datasets using S3, Glue, Athena, and Redshift.
• Implement MLOps practices for model deployment, monitoring, retraining, and version control.
• Translate complex business problems into AI/ML-driven solutions while ensuring data security and compliance.

Required Skills

• 10+ years of experience in Data Science, AI, or Machine Learning.
• Strong hands-on expertise in supervised/unsupervised learning, NLP, or deep learning.
• Advanced Python programming with Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.
• Extensive experience with AWS, specifically SageMaker, S3, Redshift, Glue, Athena, and Lambda.
• Solid foundation in statistics, predictive modeling, and ML algorithms.
• Proficiency in SQL and data visualization techniques.
• Bachelor's degree in a relevant field.

Preferred Skills

• AWS Certifications (Machine Learning – Specialty or Solutions Architect).
• Experience with Spark and real-time streaming data pipelines.
• Background in financial services or regulated industries.

Key Skills

Education

Bachelor's degree