Engineering Manager II, Marketplace Pricing

About the Role

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. The leaders of the team guide the work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior leaders within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced organizational leaders.

We are looking for an exceptional Tech Lead Manager (TLM) or Engineering Manager (EM) with a track record of extraordinary impact and with a passion for building high-velocity engineering teams and large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead a team of top-tier engineers to design, develop, and productionize advanced ML models and pricing algorithms, involving deep learning, causal modeling, and reinforcement learning. You will work with peer EMs, cross-functional partners, and managers outside the org to translate company priorities into multi-year technical strategies and cross-team platform architecture. You will solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.

What You Will Do

- Lead a team of exceptional engineers and cross-functional partners to design and deliver high-impact technical solutions to complex business problems
- Drive organizational and technical strategy as well as roadmap ownership over a multi-year horizon and lead the implementation, including executive communication and alignment, platform-level architecture decisions, and cross-team leadership
- Lead and delegate the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
- Guide tech leads on developing novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
- Hire, develop, and retain top-tier MLEs while fostering a culture centered on teamwork, technical excellence, smart risk taking, and inclusivity

Basic Qualifications

- Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
- 8+ years of experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
- Experience driving timely execution through effective delegation, empowering tech leads, and leading cross-team alignment by setting clear priorities, incorporating input from diverse stakeholders, and resolving trade-offs between short term and long term priorities
- Proficiency upholding high standards of quality, reliability, and operational excellence through efficient review processes and data-driven process improvements
- Proficiency in programming languages such as Python, Scala, Java, or Go
- Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
- Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
- Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
- Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization). Proficiency in reinforcement learning and causal machine learning

Preferred Qualifications

- 2+ years of leadership experience managing engineering teams as TLM or EM. Track record of delivering outstanding business impact for several multi-functional programs, products or platforms over multiple halves
- Proficiency translating complex business problems into multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output across multiple teams
- Excellent communication and collaboration skills to lead initiatives across multiple teams and build strong relationships with peer managers, cross-functional partners, and managers outside the org
- Experience in hiring, developing, and retaining top-tier talent, and experience in designing a team with the right composition of skills and seniority to deliver against business goals

For New York, NY-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 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. You will also be eligible for various benefits. More details can be found at the following link [](;br>
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](;br>
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.