Description

You will design and develop scalable machine learning models and end-to-end ML pipelines.

This role is on-site.

Responsibilities

• Build, train, validate, and deploy ML solutions using AWS services including SageMaker, Lambda, EC2, and S3.
• Implement efficient, reusable code for model training, evaluation, and inference.
• Develop front-end components for ML-driven applications using React.
• Lead junior developers through code reviews, architecture planning, and mentorship.
• Manage the model lifecycle, including CI/CD integration and version control.

Required Skills

• 7+ years of professional Python development experience.
• 5+ years of experience in machine learning implementation.
• 3+ years of experience working with AWS services for ML applications.
• 1+ year of experience with React.js.
• Proficiency with scikit-learn, pandas, NumPy, TensorFlow, or PyTorch.
• Deep understanding of supervised/unsupervised learning, model evaluation, and feature engineering.
• Experience deploying ML models into production environments.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

Preferred Skills

• Familiarity with MLOps practices and tools.
• Experience with Docker and Kubernetes.
• Background in financial services, healthcare, or enterprise platforms.

Key Skills

Education

Bachelor's degree