Description

Design, develop, and deploy AI/ML models and data science solutions on AWS, building end-to-end ML pipelines using SageMaker, Lambda, and ECR.

This role is on-site.

Responsibilities

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

Required Skills

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

Preferred Skills

• AWS Certifications (Machine Learning – Specialty or Solutions Architect).
• Experience with big data technologies such as Spark or exposure to streaming data pipelines.

Key Skills

Education

Bachelor's degree