Machine Learning Engineer

Purpose

The Machine Learning Engineer is responsible for development and deployment of algorithms, prediction models, and independent AI-based systems that are in line with company goals. Duties include maintenance and improvements of the models and systems.

Duties

• Design, develop, improve, and enhance prediction models and other autonomous AI-based systems;
• Research, design, and coordinate the best machine learning methodology, technology, and algorithms and introduce and deploy as needed;
• Perform coding tests, data integrity tests, unit tests, UATs, and integration tests to ensure accuracy, stability and functionality of deployed models, and provide swift fixes and repairs as needed;
• Prepare references, operating instructions, system diagrams, and maintain historical records by documenting development and revisions;
• Provide maintenance and improvements on implemented models as needed;
• Mentor junior ML engineers and contribute to team-wide knowledge sharing;

Requirements

• Ability to work in teams;
• Ability to think critically in broader spectrum, 
• Solid understanding of machine learning modeling, algorithms, and AI-based systems development;
  
• Knowledge of machine learning methodologies, deployments;
• Logical thinking trait;
• Professional development experience with Python, SQL, R etc.,;
• Experience working with frameworks such as Sklearn, TensorFlow, Keras, Pandas, Numpy, PyTorch, etc.,;
• Bachelor's or higher degree in Computer Science, Machine Learning Engineering, or related field;

Nice-to-Haves:

• Contributions to open source;
• Learnings from Stanford Machine Learning courses (Andrew NG);
• Knowledge and experience with Containerization;