Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Supports compensation due diligence, financial modeling, harmonization, and post-close integration for mergers and acquisitions. Evaluates target compensation structures, benchmarks market practices, identifies compliance and financial risks, and models salary, bonus, equity, and retention scenarios. Manages compensation programs for subsidiaries, maintains analytical dashboards and governance processes, and partners with HR, Finance, Legal, and Corporate Development to deliver executive-ready recommendations.

Leads technical talent sourcing strategy for engineering teams across North America. Responsibilities include market mapping, targeted sourcing, data-driven hiring insights, stakeholder influence, candidate advocacy, pipeline diversity, assessment-process improvements, and delivering a high-quality candidate experience in a fast-paced environment.

Leads product operations for Identity by designing go-to-market plans, operating models, rollout and testing strategies, and scalable global processes. Coordinates cross-functional teams across product, engineering, legal, tax, and support; surfaces customer and business insights; tracks post-launch metrics; and drives continuous product improvement. Requires analytical decision-making, SQL proficiency, global project management, and stakeholder leadership.

Design and build scalable ML infrastructure and backend systems for high-impact marketplace applications. Lead architecture, solve low-latency and high-correctness problems, develop and adopt engineering frameworks, and create production-ready technical roadmaps. Partner with Product, Science, and Operations while mentoring engineers and improving engineering standards. The role requires experience with ML models, foundational models or LLMs, MLOps, Kubernetes, data pipelines, distributed workflows, and large-scale scheduling.

Own and ship agentic AI products for Uber’s customer experience platform. Define product strategy, roadmaps, requirements, success metrics, and tradeoffs while partnering with Engineering, Data Science, Design, User Research, and Operations. Improve agent quality through evaluation, experimentation, simulations, observability, debugging, and human feedback. Use customer insights and performance data to iterate on AI-powered experiences and drive cross-functional execution from discovery through launch.

Manage and grow a portfolio of small and medium-sized restaurant partners on Uber Eats. Build long-term relationships, negotiate solutions, resolve merchant issues, use data and KPIs to identify growth opportunities, drive adoption of platform features and marketing services, and collaborate with operations, marketing, and product teams. The hybrid San Francisco role requires quarterly travel to Seattle.

Own sales compensation strategy, incentive plan design, job architecture, leveling, benchmarking, and compensation analytics. Partner with Sales Operations, HR, Finance, Legal, and leadership to model commission structures, assess financial risk, forecast ROI, analyze plan effectiveness, and communicate compensation changes. The role requires strong financial modeling, data analysis, stakeholder influence, and experience in high-growth technology environments.

Leads Uber Advertising’s US sales organization, owning revenue strategy, commercial execution, quota and pipeline discipline, forecasting, and operational scaling. Partners with Product, Engineering, Marketing, Finance, Legal, and Operations to shape advertising products, inventory, measurement, pricing, and go-to-market strategy. Builds a high-performance culture, recruits and develops multi-tier sales leadership, manages major advertiser and agency relationships, and drives growth across a rapidly scaling ad-tech marketplace.

Analyze employee, survey, HRIS, and behavioral data to deliver insights on engagement, retention, performance, and organizational health. Partner with business leaders and HR teams as an analytics consultant, build dashboards and repeatable analyses, interpret employee listening results, and communicate recommendations through clear narratives and visualizations. Support scalable self-service reporting and improve measurement of employee experience.

Develop and own end-to-end machine learning models for Uber Freight’s marketplace, including cost prediction, booking probability, demand elasticity, pricing, matching, recommendations, and optimization. Partner with backend engineers to deploy models to production and ensure reliable performance. Apply predictive modeling, causal inference, constrained optimization, reinforcement learning, and marketplace design to solve complex logistics problems.