Software Engineer II role at Uber focused on designing, building, and operating end-to-end features for the AdTech tech stack. This involves creating scalable data pipelines using big data technologies, optimizing ad spend through experimentation, and productionizing ML models. The role requires collaboration with cross-functional teams and leveraging internal Uber technologies like Michelangelo (ML) and Piper (Data orchestrator).

Staff Machine Learning Engineer at Uber Marketplace focused on optimizing rider & driver matching using optimization, machine learning, and causal inference. The role involves building scalable ML libraries and systems, improving the ML Platform ecosystem, and collaborating with the ML community. Requires PhD or equivalent, 5+ years of experience, and proficiency in modern ML algorithms and frameworks.

Software Engineer to join the Matching ML Platform team, focusing on building and scaling a low-latency platform for real-time matching decisions, evolving the ML platform for inference and experimentation, and designing extensible architectures for ML-powered matching capabilities.

Staff Machine Learning Engineer at Uber on the Marketplace Signals team, focused on developing and optimizing ML models for marketplace signals like ETA predictions, supply availability, and demand forecasts. The role involves building scalable systems for these signals, leveraging ML techniques, and working with real-time data and distributed systems. Requires a strong background in ML, statistics, optimization, and experience with ML frameworks and data pipelines.

Staff Software Engineer on Uber's ML Serving team within the AI Platform, focusing on infrastructure for real-time ML and generative AI inference at scale. Responsibilities include defining technical direction, leading cross-team initiatives, and designing foundational architectures for thousands of models in production.

Software Engineer II role focused on building backend systems for automated retail intelligence, processing image data, orchestrating model inference, and converting predictions into inventory signals. Requires experience with scalable data pipelines, backend service development, and system reliability.

Senior Machine Learning Engineer at Uber Direct, focusing on building and productionizing ML systems for real-time logistics operations, including ETA prediction, demand forecasting, and dispatch optimization. The role involves the end-to-end ML lifecycle, from data exploration to deployment and monitoring, with an emphasis on scalable ML systems and driving business impact.

Software Engineer II focused on designing, developing, optimizing, and productionizing machine learning models and systems at scale for Uber's marketplace, maps, and membership platforms. Responsibilities include writing efficient code for low-latency, high-reliability models, implementing monitoring systems, and collaborating with cross-functional teams. Requires experience with the full ML lifecycle, including deployment and orchestration.

Software Engineer II on the Incentive Platform team at Uber, focusing on building and scaling a business-critical, ML-powered incentive ecosystem for drivers and couriers. The role involves architecting and developing high-throughput, real-time distributed systems and ML inference infrastructure to optimize incentive generation and delivery.

Staff Engineer on the Core Infrastructure Platform team at Uber, focusing on the architecture and evolution of systems powering Uber's global business. The role involves leading the development of backend solutions for cloud-native, secure, reliable, and hyperscale-efficient ecosystems, supporting massive compute demands for Generative AI and Autonomous Vehicle data. Responsibilities include architectural evolution, driving efficiency, modernizing for multi-cloud, integrating AIOps & Automation, championing security, and influencing cross-functional teams to support large-scale AI/ML workloads.

Senior Staff Engineer to lead the technical strategy and evolution of Uber’s Core Infrastructure Platform, focusing on compute, foundations, and software networking. The role involves architecting for extreme scale, optimizing fleet utilization, scaling GPU pools for Generative AI, modernizing the data plane, and integrating AI-driven automation (AIOps) into the infrastructure.

Staff Software Engineer role focused on architecting and scaling distributed backend systems for media ingestion, processing, intelligence, and delivery. The role involves improving performance, reliability, and cost efficiency of high-throughput media pipelines, and designing infrastructure for efficient integration and execution of ML inference workloads within these media systems. It also includes driving technical strategy and mentoring engineers.

Software Engineer II to join the Data Security & Governance engineering team, focusing on building distributed backend and AI-powered systems for data protection and safe adoption of ML/GenAI. The role involves designing and building scalable systems, handling transactions, developing intelligent privacy and security strategies, and working with GenAI and Model Context Protocol.

This role focuses on designing and scaling real-time dynamic pricing systems for Uber, involving large-scale, low-latency systems that handle millions of QPS. It requires expertise in distributed systems, optimization, and ML, with a focus on scaling model inference and real-time feature serving for pricing decisions.