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

Own a portfolio of education partners to drive retention, renewals, and expansion. Build engagement programs and trainings, monitor usage and health signals, and coordinate cross-functionally to resolve partner needs. Travel 25–35% and act as strategic advisor and customer advocate to improve adoption and long-term outcomes.

Design, build, evaluate, and deploy ML systems for search, recommendations, embeddings, and personalization. Work with large datasets to create features, train models, run experiments, monitor production models, and improve reliability, latency, and marketplace outcomes in collaboration with cross-functional partners.

The Engagement Management Lead will drive customer relationships by managing the full engagement lifecycle, ensuring successful implementation, and translating customer needs into actionable programs.

As a Machine Learning Engineer I, you will develop and deploy machine learning systems for core relevance signals, collaborating with engineers and product teams.

Manage a team of Strategic Project Leads in delivering high-stakes AI data projects while ensuring operational excellence and performance metrics.

Build AI-driven workflows, automations, and agents for GTM teams; mine and score prospect signals; implement and maintain Salesforce- and warehouse-integrated systems using Python, SQL, BigQuery, Clay, and orchestration tools; own end-to-end delivery, monitoring, and documentation.

Lead and scale a Growth Engineering team owning acquisition, activation, retention, and notification systems. Build a modular, extensible growth platform for experimentation and personalization, drive architecture and technical strategy, partner with Product/Data/Marketing, raise engineering quality and observability, hire and develop leaders, and deliver high-impact growth outcomes.

Build and maintain Reinforcement Learning Environments platform: implement backend features and frontend interfaces, support data pipelines for model training, improve system reliability and performance, and collaborate with senior engineers to deliver modular workflow domains.

Build and operate shared ML/AI infrastructure: data pipelines, feature stores, training, model serving and LLM platform work. Scale inference and training (GPU, batching, autoscaling), enable evaluation and post-training workflows, and partner with AI, data science, and product teams to productionize models and improve platform reliability and developer experience.

Lead product analytics for Handshake's recruiting marketplace: define metrics, own analytics strategy, run experiments, evaluate ML models, perform cohort and funnel analyses, build dashboards, and partner with product, engineering, and analytics engineering to drive data-informed growth and pricing decisions.