Hybrid Machine Learning (AI) Engineer

About the role

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

Key responsibilities

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

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 version control and CI/CD pipelines.

Required skills

• Python
• TensorFlow
• PyTorch
• MLflow
• Kubeflow
• SageMaker
• AWS
• GCP
• 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 collaborative environment.
• Competitive compensation ranging from $200K to $500K per year.