Sr Machine Learning Engineer

About the Team

Basic Qualifications

• 5+ years of hands-on professional experience designing, training, and operating production ML models at scale.
• Proactive and strong analytical mindset with a passion for uncovering insights from complex data distributions to drive technical decision-making and project buy-in.
• Advanced proficiency in Python and mainstream machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
• Solid theoretical foundation in classic and modern ML algorithms, including and not limited to gradient-boosted trees (XGBoost, LightGBM), deep neural networks, and statistical modeling.
• Proven record of taking complex ML systems end-to-end from initial problem formulation and offline validation to large-scale production deployment.
• Practical experience developing automated feature engineering pipelines, using feature store technologies, model monitoring platforms, and executing controlled online A/B testing in production.

Preferred Qualifications

• PhD candidate 3+ years of industry experience
• Experience with geospatial libraries (e.g., H3, S2 Cell).
• Experience with Graph Neural Networks (GNNs), and/or deep learning recommendation systems.
• Demonstrated ability to drive cross-functional technical initiatives, mentor junior engineers, and deliver complex multi-phase engineering projects.
• Familiarity with distributed data processing systems (e.g., Spark, Ray, Flink) and foundational concepts in two-sided marketplace optimization.

Responsibilities

• For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
• For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
• For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
• As a Senior Machine Learning Engineer on the Deliverability team, you will drive the technical vision, end-to-end design, and productionization of core ML systems powering global delivery marketplace decisions. Specifically, you will:
• Product & Domain ML Architecture: Architect and translate complex marketplace challenges into high-throughput, large scale ML solutions for delivery zone optimization.
• Design & Train Core Models: Develop, evaluate, and continuously refine state-of-the-art machine learning models that dynamically optimize merchant delivery coverage, balancing conversion, order volume, and fulfillment efficiency.
• Production Pipelines & ML Infrastructure: Engineer, deploy, and operate scalable ML inference pipelines, feature stores, model serving infrastructure, and automated retraining workflows handling high-throughput global delivery evaluations.
• Marketplace Optimization & Experimentation: Lead data-driven investigations to diagnose marketplace inefficiencies, execute online A/B testing and leverage telemetry to drive core business metrics.
• Cross-Functional Technical Leadership: Partner closely with Product Management, Data Science, Operations, and Core Infrastructure teams to align technical roadmaps and define cross-platform ML standards.