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

Design, implement, and integrate machine learning models and data pipelines for a programmatic DSP. Support model development for prediction, forecasting, and fraud detection; prepare large datasets; collaborate with cross-functional teams; document experiments and maintain reproducibility.

Lead design and implementation of a global revenue operating system: forecasting, territory design, incentive modeling, GTM enablement, tech-stack optimization, lifecycle documentation, and retention frameworks to scale predictable global revenue and reduce manual operational work.

Lead design and implementation of production ML systems for low-latency ad use cases (bidding, ranking, pacing, fraud). Build training and feature pipelines, real-time inference services, and ML team. Partner with engineering and product, own model experimentation, evaluation, monitoring, and deployment at scale.

Lead end-to-end launch and operation of multiple new ventures from concept to monetization. Use AI-native tools to spec, prototype, ship, measure, and iterate rapidly. Own GTM, onboarding, pricing, analytics, and customer development while partnering daily with the CEO and coordinating small engineering teams.

Lead global Customer Success to protect and grow a $xxxM revenue base by driving retention (NRR), account expansion, standardized onboarding, forecasting governance, and product feedback loops. Scale and enable distributed teams with playbooks, coaching cadences, and documented workflows to ensure first-time-right launches and predictable revenue outcomes.

Analyze large advertising datasets to optimize programmatic campaigns, identify growth opportunities, run trend and opportunity analyses, collaborate with Product/Data Science/Engineering, communicate analytics to clients, and drive business development through data-driven insights.

Design, build, and operate large-scale, fault-tolerant real-time and batch data pipelines powering an ad-tech DSP. Collaborate with engineers and data scientists to define data models and SLAs, optimize performance and capacity, enforce data quality and monitoring, mentor engineers, and evaluate new data technologies to scale analytics and ML workloads.

Serve as the CEO's strategic operator and force-multiplier: lead CEO-level projects (M&A, partnerships, board/investor materials), run executive operating cadence, build dashboards, coordinate cross-functional initiatives, draft CEO communications, and translate between technical and business teams to drive execution and accountability across the company.

Lead and scale a global hunter sales organization to achieve net-new revenue targets. Build and execute non-gaming GTM, ABM, and tiered sales plans; enforce forecasting integrity, pipeline governance, and documentation. Hire, enable, coach, and ramp senior sales talent while creating feedback loops to Product to expand PMF and accelerate market penetration.

Serve as the technical bridge between Sales, Customers, and Engineering to support pre-sales consulting and post-sales implementation of the company's DSP. Guide integrations, troubleshoot campaign/data issues, manage technical deployments (tracking, audience ingestion, reporting), and provide product feedback, documentation, and optimization recommendations.