• Design, implement, and deploy machine learning models to optimize software build systems, including caching, task distribution, and execution workflows • Work with large datasets to identify patterns, anomalies, and insights that inform decisions for improving build processes and remote execution • Develop predictive models to optimize build times, cache hit rates, and system resource utilization • Conduct experiments to improve the efficiency of build systems through data-driven decisions, leveraging AI/ML techniques such as reinforcement learning and optimization • Collaborate with cross-functional teams (engineering, product, and operations) to translate business problems into AI/ML-driven solutions • Analyze customer usage data to identify opportunities for feature improvements and innovations within the NativeLink platform • Develop custom algorithms for performance monitoring, anomaly detection, and optimization of CI/CD pipelines • Build, test, and validate machine learning models using a variety of techniques, ensuring they are scalable, robust, and interpretable • Build and maintain data pipelines to support model training, testing, and deployment in production environments • Communicate findings and insights to both technical and non-technical stakeholders in a clear and actionable way