Hybrid Machine Learning (AI) Engineer

About the role

We are seeking a Machine Learning (AI) Engineer to design, develop, and deploy intelligent models that power core product features. The role is hybrid, allowing you to work remotely while collaborating with cross‑functional teams to deliver scalable AI solutions that improve user experience and operational efficiency.

Key responsibilities

• Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch.
• Develop and maintain data pipelines to ensure high‑quality inputs for model training and evaluation.
• Implement MLOps practices, including 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

• Proficiency in Python and deep‑learning frameworks such: TensorFlow and PyTorch.
• Experience with MLOps tools like MLflow, Kubeflow, or SageMaker.
• Strong background in data preprocessing, feature engineering, and model evaluation metrics.
• Familiarity with cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure.
• Knowledge of 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