Lead strategically important initiatives: Turn ambiguous problems into actionable technical strategies, and drive execution across teams from problem formulation and offline evaluation through experimentation, production deployment, and ongoing improvement.
Advance personalization and optimization: Design models and algorithms that improve incentive relevance, estimate incremental impact, and optimize decisions under business and operational constraints.
Architect scalable ML systems: Guide—and contribute directly to—the design and implementation of end-to-end ML systems, spanning data and feature pipelines, model training, inference, and monitoring, with a high bar for reliability, scalability, and maintainability.
Connect scientific rigor to business outcomes: Establish strong approaches to model evaluation, experimental design, and causal measurement, balancing short-term results with long-term consumer value and sustainable growth.
Translate emerging techniques into practical advances: Evaluate where reinforcement learning, foundation models, and generative AI can meaningfully improve our products, and lead promising approaches from exploration to production.
Build alignment across functions: Partner with product management, data science, operations, and engineering leaders to prioritize opportunities, make technical tradeoffs, and deliver shared outcomes.
Multiply the impact of others: Mentor engineers and technical leaders, raise the quality of technical decision-making, and build reusable capabilities that accelerate work across teams.
Basic Qualifications
Masters degree or Ph.D in Computer Science, Engineering, Mathematics
12+ years of ML experience, including significant work on large-scale deep learning systems.
Demonstrated ownership of high-impact ML systems such as search, recommendations, personalization, targeting.
Proven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level.
Strong product intuition and ability to connect model improvements to business outcomes.
Preferred Qualifications
Track record of successfully launching multi-year, multi-org ML initiatives that drove step-change business outcomes.
Successfully championed and driven the adoption of multi-year technical roadmaps across multiple large engineering organizations.
Elevated engineering standards through mentorship and technical leadership, establishing org-wide best practices.
For New York City, NY-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 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.
