Machine Learning (AI) Engineer – Hybrid

About the role

We are seeking a Machine Learning (AI) Engineer to design, train, and deploy intelligent models that power core product features. The position is hybrid, allowing 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.
• Develop and maintain data pipelines to ensure high‑quality input for model training and evaluation.
• Implement MLOps practices (MLflow, Kubeflow, SageMaker) for model deployment, monitoring, and version control.
• Collaborate with data scientists and software engineers to integrate AI capabilities into production systems.
• Conduct performance benchmarking and A/B testing 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 a collaborative technical environment.
• Competitive compensation package.