Machine Learning Engineer

Job title: Machine Learning Engineer

About the Role We are seeking a highly experienced Machine Learning Engineer to join our MarTech team and drive innovation within our ML ecosystem. You will own end-to-end development, optimization, and deployment of production-ready ML models and feature engineering pipelines, with a strong emphasis on operationalizing models that power the customer experience. A solid understanding of ML engineering best practices and proven experience building scalable ML systems and feature pipelines is essential.

What You'll Do

• Design, develop, and deploy machine learning solutions and feature engineering pipelines.
• Configure, test, debug, deploy, document, and maintain ML pipelines, models and feature engineering modules while adhering to development best practices and quality standards.
• Work closely with data scientists, data engineers, and solution architects to develop technical design specifications for ML programs, focusing on efficient feature engineering and model deployment.
• Analyze large-scale datasets and validate the proposed ML solutions with architectural design and business needs, ensuring model performance meets target metrics.
• Responsible for troubleshooting and issue analysis across the ML stack, including feature pipelines, model training, inference, and model monitoring, as well as coding, testing, and implementing model enhancements.
• Demonstrate a strong understanding of supervised, unsupervised, ensemble, and deep learning algorithms to design and implement effective ML solutions, with experience in feature engineering, model evaluation, and continuous performance optimization to meet business targets.
• Implement and maintain MLOps practices.

What We're Looking For

• Strong experience designing, building, and deploying production-ready ML models and feature pipelines.
• Proven track record of building scalable ML systems and feature pipelines.
• Solid understanding of ML engineering best practices and ability to operationalize ML models.
• Experience collaborating with data scientists, data engineers, and solution architects to develop technical design specifications for ML programs, focusing on efficient feature engineering and model deployment.
• Ability to analyze large-scale datasets and validate ML solutions against architectural design and business needs, ensuring target metrics are met.
• Troubleshooting across the ML stack including feature pipelines, model training, inference, monitoring, and implementing model enhancements.
• Knowledge of supervised, unsupervised, ensemble, and deep learning algorithms; experience in feature engineering, model evaluation, and continuous performance optimization.
• Interest in implementing and maintaining MLOps practices.

Nice to Have

• Optional/preferred qualifications (only if mentioned)

Compensation & Benefits

• Salary range, benefits, perks (only if mentioned)