The Staff Machine Learning Engineer will be part of a new team within the DashPass organization at DoorDash, focusing on leveraging AI and advanced machine learning to enhance personalization efforts across the subscriber journey. This role involves designing and developing large-scale ML systems aimed at improving subscriber acquisition and retention strategies. The engineer will work closely with Product, Data Science, and Engineering teams to create impactful models and frameworks. This position is ideal for someone who enjoys solving complex optimization problems and has a strong background in machine learning.

• M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field.
• 8+ years of industry experience building production-scale ML systems.
• Proficiency in using AI coding tools in the full software development lifecycle.
• Strong understanding of probability theory, statistics, and machine learning fundamentals.
• Strong programming skills in Python, Java, or C++, and experience with ML frameworks such as TensorFlow, PyTorch, or XGBoost.
• Proven ability to lead cross-functional initiatives and drive complex technical projects end-to-end.
• Excellent communication skills to explain technical concepts to diverse audiences.

• Contribute to causal inference modeling to measure the impact of subscriber acquisition and retention strategies.
• Develop incentive optimization frameworks that personalize rewards to improve spend efficiency.
• Create budget allocation and forecasting models to identify optimal spend across acquisition, referrals, and retention.
• Partner closely with Product, Data Science, and Engineering teams to design experiments and production ML systems.
• Provide technical mentorship and guidance to engineers and cross-functional partners.
• Build and deploy 0→1 ML systems that enhance subscriber outcomes and marketplace health.
• Set best practices for model training, evaluation, deployment, and monitoring.