Machine Learning Engineer

We are looking for a Machine Learning Engineer I with strong Python programming skills to develop, deploy, and optimize machine learning solutions for ad monetization and personalization. You'll collaborate with cross-functional teams to build scalable ML pipelines, enhance recommendation and targeting models, and deliver production-ready AI solutions that improve user engagement and business outcomes.

• Develop, train, and deploy machine learning models for personalization, recommendation, and customer experience applications.
• Build and maintain scalable data pipelines for feature engineering, model training, validation, and inference.
• Collaborate with machine learning scientists, data engineers, and software engineers to transition research models into production.
• Enhance recommendation and ranking models using customer behavioural and transactional data.
• Monitor, evaluate, and improve model performance through experimentation, A/B testing, and data-driven analysis.
• Write clean, efficient, and maintainable Python code following software engineering best practices.
• Optimize machine learning workflows to improve customer engagement and support business objectives.
• Participate in model deployment, monitoring, troubleshooting, and continuous improvement initiatives.
• Document machine learning processes, model performance, and technical solutions to support collaboration and knowledge sharing.

• Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, or a related field.
• 1-3 years of experience in machine learning, including internships, research, or professional experience.
• Strong programming skills in Python.
• Solid understanding of machine learning concepts, including supervised learning, feature engineering, model evaluation, classification, and regression.
• Experience with machine learning frameworks such as Scikit-learn, Tensor Flow, or PyTorch.
• Experience working with SQL and large datasets.
• Familiarity with Git and software development best practices.

• Build and deploy production-ready machine learning models at scale.
• Gain hands-on experience with recommendation systems, personalization, and ranking algorithms.
• Learn best practices for feature engineering, model monitoring, and performance optimization.
• Work with large-scale data processing and modern machine learning pipelines.
• Develop expertise in experimentation frameworks, A/B testing, and data-driven decision-making.
• Collaborate with experienced machine learning engineers, software engineers, and data scientists on real-world AI solutions.
• Strengthen your understanding of MLOps concepts, including model deployment, versioning, and lifecycle management.
• Improve your software engineering skills by contributing to scalable, maintainable, and production-quality codebases.

GCS is acting as an Employment Business in relation to this vacancy.