Machine Learning (AI) Engineer (Hybrid)

About the role

We are seeking a Machine Learning (AI) Engineer to design, develop, and deploy intelligent models that power core product features for a global software leader. The position is hybrid, allowing you to work remotely while collaborating closely with cross‑functional teams.

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 seamless deployment and monitoring.
• Collaborate with data scientists and software engineers to integrate AI capabilities into production systems.
• Conduct performance benchmarking, A/B testing, and model validation to measure business impact.

Required profile

• Strong background in machine learning model development and evaluation.
• Experience with cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure.
• Proficiency in software engineering best practices, including version control (Git) and CI/CD pipelines.
• Ability to work independently and as part of a collaborative, fast‑paced team.

Required skills

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

What we offer

• Opportunity to work with cutting‑edge AI tools and large‑scale datasets.
• Competitive compensation package.
• Collaborative environment with global impact.