Machine Learning (AI) Engineer (Hybrid)

Role Overview

Machine Learning (AI) Engineer (Hybrid) to design, train, and deploy machine learning models that power core product features. You’ll collaborate with cross-functional teams to deliver scalable AI solutions for production systems.

Responsibilities

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

Required Skills & Qualifications

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

Nice-to-Haves

• Not explicitly stated (access to cutting-edge tools/datasets is mentioned).