Remote Advertising ML Engineer – Personalization at Scale

GCS Recruitment; Indianapolis (IN); On-site; USD 90,000 - 120,000; Full time

Job summary

GCS Recruitment is seeking an Advertising ML Engineer to join our growing team as a Machine Learning Engineer I. This remote USA role offers early-career professionals a chance to build ML solutions that scale and improve personalization and recommendations.

You will collaborate with data scientists and software engineers to productionize models, build data pipelines, and monitor performance with experiments and A/B tests, while writing clean Python and applying best practices.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field.
• 1–3 years of relevant experience (internships, research, projects, or professional work).
• Proficient in Python.
• Strong ML fundamentals: supervised learning, classification, regression, feature engineering, evaluation.
• Experience with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Experience with SQL and large datasets.
• Familiar with Git and software development practices.
• Strong analytical and problem-solving skills.

Responsibilities

• Develop, train, and deploy ML models for personalization and recommendations.
• Build scalable data pipelines for feature engineering, model training, evaluation, and inference.
• Collaborate with data scientists and software engineers to productionize research.
• Improve recommendation and ranking models using large-scale data.
• Monitor model performance with experimentation, A/B testing, and data-driven analysis.
• Write clean, maintainable Python code following software engineering best practices.
• Support initiatives that enhance customer engagement and business outcomes through ML solutions.

Job description

GCS Recruitment is seeking an Advertising ML Engineer to join our growing team as a Machine Learning Engineer I. This remote USA role offers early-career professionals a chance to build ML solutions that scale and improve personalization and recommendations.

You will collaborate with data scientists and software engineers to productionize models, build data pipelines, and monitor performance with experiments and A/B tests, while writing clean Python and applying best practices.