Machine Learning (AI) Engineer (Hybrid)

About the role

We are seeking an experienced Machine Learning (AI) Engineer to design, develop, and deploy intelligent models that power core product features. This hybrid position allows you to work remotely while collaborating with cross‑functional teams to deliver scalable AI solutions.

Key responsibilities

• Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch.
• Build and maintain robust data pipelines for high‑quality model input.
• Implement MLOps practices with tools such as MLflow, Kubeflow, or SageMaker to streamline 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 with cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure.
• Familiarity with software engineering best practices, including Git and CI/CD pipelines.

Required skills

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

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 ranging from $200K to $500K per year.