Machine Learning (AI) Engineer – Hybrid

About the role

We are seeking a Machine Learning (AI) Engineer to design, develop, and deploy intelligent models that power core product features for a global software leader. The position is hybrid, allowing you to collaborate with cross‑functional teams while working remotely.

Key responsibilities

• Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch.
• Build and maintain robust data pipelines to ensure high‑quality training data.
• Implement MLOps practices with tools such as MLflow, Kubeflow, or SageMaker for seamless deployment, monitoring, and version control.
• Collaborate with data scientists and software engineers to integrate AI capabilities into production systems.
• Conduct performance benchmarking, A/B testing, and impact analysis to validate model effectiveness.

Required profile

• Strong background in data preprocessing, feature engineering, and model evaluation metrics.
• Experience working with cloud platforms (AWS, GCP, or Azure) to build scalable AI infrastructure.
• Familiarity with software engineering best practices, including Git version control and CI/CD pipelines.

Required skills

• Python
• TensorFlow
• PyTorch
• MLflow, Kubeflow, or SageMaker
• AWS, GCP, or Azure
• Git
• CI/CD pipelines

What we offer

• Opportunity to work with a global leader in software development.
• Access to cutting‑edge tools, large datasets, and a collaborative environment.
• Competitive compensation package with a salary range of $200K‑$500K per year.