Machine Learning (AI) Engineer (Hybrid)

About the role

We are seeking a Machine Learning (AI) Engineer to design, develop, and deploy advanced AI models that power core product features for a global software development leader. The role is hybrid, offering flexibility while collaborating with cross‑functional teams to deliver scalable, high‑impact solutions.

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 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 model evaluation to validate business impact.

Required profile

• Strong experience in developing and deploying machine learning models.
• Proficiency with MLOps tools and cloud platforms (AWS, GCP, or Azure).
• Solid understanding of software engineering best practices, including Git and CI/CD pipelines.

Required skills

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

What we offer

• Opportunity to work with cutting‑edge AI technologies and large‑scale datasets.
• Collaborative environment within a global leader in software development.
• Competitive compensation ranging from $200K to $500K per year.