• Design, build, evaluate, and ship LLM based solutions that will enable our users to have more adaptive control of their content • Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways • Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users • Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization • Be part of an active group of machine learning practitioners

• Lead the development + implementation of real-time feature detection and anomaly detection models • Generate data characteristic requirements for real-time data processing pipelines • Prepare technical documentation, reports, and specifications • Collaborate with cross-functional teams including project managers, technicians, and other engineers • Perform testing, troubleshooting, and quality assurance on systems or products • Ensure compliance with safety regulations, industry standards, and company policies

• Build, deploy, and optimize the machine learning services that power the Tebra platform • Write high-quality, production-grade software for data ingestion, feature extraction, and model inference • Implement robust CI/CD pipelines, automated testing, and comprehensive logging for deployed models • Construct and maintain specific data pipelines for training and inference • Develop reusable software modules and utilities to streamline the development process • Translate business requirements into technical specifications • Monitor the daily performance of production models and debug incidents

• Translate complex business problems into solutions that leverage end-to-end, production-level machine learning systems • Develop, iterate on, and productionize machine learning models, owning both model logic and supporting systems. • Implement and own backend pricing services and APIs consumed by the Lime App. • Architect and build scalable, reliable platforms and services that power pricing decisions and enable new product initiatives. • Build trust with leadership to influence the company's pricing strategy through reasoning and communication of model performance and technical vision • Collaborate with other Software Engineers and Data Scientists to raise the bar on ML standards and Engineering Excellence • Mentor and support engineers on the team, helping grow technical depth and develop future leaders.