As a Senior Machine Learning Engineer at GoDaddy’s Commerce Data & ML team in Bulgaria, you will be instrumental in developing production-grade ML pipelines and scalable systems to support fraud mitigation, customer insights, and AI-driven experiences. You will design, build, and maintain robust ML pipelines for batch and real-time inference using AWS SageMaker Pipelines, EventBridge, MLflow, and feature stores. Your role includes collaborating with Data Scientists, Engineers, and stakeholders to implement, monitor, and optimize ML workflows, including model training, evaluation, drift detection, and deployment. You will enhance and manage CI/CD pipelines for ML models, oversee model promotion, retraining workflows, and ensure seamless integration across different environments. Leading end-to-end delivery of ML features from architecture and implementation to monitoring and iteration will be part of your responsibilities, alongside mentoring junior engineers and promoting best practices. You will support operational excellence by participating in on-call rotations, production incident response, post-mortems, and contribute to the planning and scoping of ML initiatives. Required experience includes 7+ years in software with 5+ in ML engineering, pipelines, or applied ML, proficiency with AWS SageMaker Studio, Tecton, Python, ML frameworks like scikit-learn, PyTorch, TensorFlow, experience with MLflow, SageMaker Pipelines, EventBridge, Glue, EMR, Flink, and familiarity with CI/CD for ML workflows. Bonus skills include expertise in dual-model pipelines, business-aligned success metrics, fraud detection, risk modeling, financial domains, prompt engineering, LLM integration, and backend development in Java, Scala, or Go. GoDaddy supports diversity, equity, inclusion, offers competitive benefits, and embraces remote work modes, making it a great place to grow your career in ML engineering.