Machine Learning (AI) Engineer (Hybrid)

Role Overview

We are hiring for one of our clients, seeking an AI/ML Engineer to develop and deploy machine learning models that power core product features. The role involves collaborating with cross-functional teams to design scalable AI solutions that enhance user experience and operational efficiency.

Key Responsibilities

• Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch frameworks.
• Develop and maintain data pipelines to ensure high-quality input for model training and evaluation.
• Implement MLOps practices to streamline 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 Skills & Qualifications

• Proficiency in Python, TensorFlow, and PyTorch for model development and training.
• Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for deployment and monitoring.
• 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 version control (Git) and CI/CD pipelines.

More About the Opportunity

This role offers a unique opportunity to work with a global leader in the Software Development industry, contributing to the advancement of AI-driven product solutions. The position involves solving complex technical challenges in a collaborative environment with access to cutting-edge tools and datasets.