Machine Learning (AI) Engineer (Hybrid)

Role Overview

Machine Learning (AI) Engineer (Hybrid) role developing and deploying machine learning models that power core product features. You will collaborate with cross-functional teams to build scalable AI solutions that improve user experience and operational efficiency.

Responsibilities

• Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch
• Build and maintain data pipelines to support high-quality training and evaluation data
• Apply MLOps practices for model deployment, monitoring, and version control
• Partner with data scientists and software engineers to integrate AI into production systems
• Run performance benchmarking and A/B testing to validate accuracy and business impact

Required Skills & Qualifications

• Proficiency in Python, TensorFlow, and PyTorch
• MLOps experience with MLflow, Kubeflow, or Amazon SageMaker
• Strong foundation in data preprocessing, feature engineering, and model evaluation metrics
• Cloud experience with AWS, GCP, or Azure
• Software engineering best practices including Git and CI/CD pipelines

Nice-to-Haves

• Experience with production ML monitoring and model versioning workflows

Work Mode

• Hybrid / Remote (location listed as United States)