About the role

Role overview

Machine Learning (AI) Engineer (Hybrid)

You’ll develop and deploy machine learning models that power core product features. The work involves designing scalable AI solutions with cross-functional teams to 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 model training and evaluation
Apply MLOps practices for deployment, monitoring, and model/version control
Collaborate 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
Experience with MLOps tools such as MLflow, Kubeflow, or Amazon SageMaker
Strong background in data preprocessing, feature engineering, and model evaluation metrics
Familiarity with cloud platforms: AWS, GCP, or Azure
Software engineering best practices: Git and CI/CD pipelines

Nice to have (implied)

Experience integrating ML models into end-to-end production systems
Demonstrated ability to improve user experience and operational efficiency using ML

About Hired

Hired is a company in the software development and hiring space, connecting candidates with clients that need specialized engineering talent. The posting describes a role with a client building AI-driven product features using machine learning models in production environments.