Machine Learning (AI) Engineer (Hybrid)

Role Overview

Machine Learning (AI) Engineer to design, train, and deploy machine learning models that power core product features. You’ll work 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 for high-quality training/evaluation data
• Apply MLOps to support deployment, monitoring, and model version control
• Collaborate with data scientists and software engineers to integrate AI into production systems
• Benchmark model performance and run 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 metrics
• Familiarity with cloud platforms: AWS, GCP, or Azure
• Software engineering best practices including Git and CI/CD

Nice-to-haves

• Experience integrating ML models into production systems and operationalizing models at scale