The Senior Machine Learning Engineer position at GoDaddy involves working remotely from Bulgaria to support the Commerce Data & ML team which powers intelligent and secure experiences for GoDaddy’s Commerce division. The role is deeply integrated with Data Science and Risk teams to build and maintain production ML Risk Models such as Transaction Risk Scoring and Merchant Risk Models and to support data-driven marketing and customer segmentation through reliable pipelines and predictive models. The team employs a robust ML platform built on AWS SageMaker Pipelines, Tecton feature store, Glue, GitHub Actions, and MLflow supporting batch and real-time inference and has recently begun developing prompt engineering workflows for large language model (LLM) powered chatbots. Responsibilities include designing, building, and maintaining robust ML pipelines using tools such as SageMaker Pipelines, EventBridge, MLflow, and feature stores; collaborating with Data Scientists, Engineers, and stakeholders to implement, monitor, and optimize ML workflows including model training, evaluation, drift detection, and deployment; enhancing and managing CI/CD pipelines for ML models; leading end-to-end delivery of ML features from architecture through implementation to monitoring and iteration; mentoring junior engineers and promoting best practices; and supporting operational excellence via on-call rotations, production incident response, post-mortems, and planning ML initiatives. The role requires 7+ years in the software industry with at least 5 years focused on ML engineering and applied machine learning, hands-on experience with AWS SageMaker Studio, Tecton, Python, and ML frameworks like scikit-learn, PyTorch, and TensorFlow; experience with experiment tracking (MLflow), ML workflow orchestration (SageMaker Pipelines, EventBridge), and batch and real-time inference pipelines; familiarity with data preparation and streaming tools like Glue, EMR, Flink; strong grasp of CI/CD for ML model deployment and endpoint configuration; and excellent collaboration skills across teams. Preferred qualifications include experience building dual-model pipelines, knowledge of business-aligned success metrics, experience with fraud detection and risk modeling, familiarity with LLM prompt engineering, and backend or data engineering skills in Java, Scala, or Go. GoDaddy offers a comprehensive total rewards package including paid time off, retirement savings plans, bonus/incentives, equity grants, employee stock purchase plan, competitive health benefits, family-friendly benefits including parental leave, and Employee Resource Groups supporting a diverse and inclusive culture. The company is committed to equity, diversity, inclusion, and belonging in all aspects of work and customer experience and is an equal opportunity employer.