Top Tech Jobs & Startup Jobs in Los Angeles, CA

Own ZipRecruiter’s job seeker messaging product across email and push channels. Set portfolio strategy, optimize message selection and frequency, analyze KPIs, run experiments, and balance engagement with trust and retention. Partner with engineering, data science, matching, marketplace, and employer product teams. Lead deliverability, compliance, sender reputation, and opt-in systems while using machine learning, ranking, and recommendation models to improve outcomes.

Own ZipRecruiter’s job seeker messaging product across email and push notifications. Set portfolio strategy, optimize message selection and frequency, manage experiments, and improve activation, retention, applications, revenue, deliverability, compliance, and sender reputation. Partner with engineering, data science, machine learning, marketplace, and employer-facing teams while conducting user research and representing job seekers.

Leads ZipRecruiter’s Marketplace Decision Science team as a player-coach, managing and developing decision scientists while personally conducting high-impact analyses. Owns marketplace quality metrics, experimentation standards, tradeoff frameworks, forecasting, and ROI modeling. Partners with Product, Engineering, Finance, and GTM leaders to shape strategy, evaluate ranking changes, quantify long-term impact, and communicate insights to executives. Requires strong product analytics, data science, experimentation, business, and people-management experience.

Lead design and management of sales commission plans and quarterly goal-setting. Perform ROI and data-driven analysis to align incentives with profitable growth. Advise executives, partner with cross-functional teams on product launches, and champion initiatives to improve incentive effectiveness.

Own the vision, strategy, roadmap, and execution for an SMB product area focused on candidate delivery or proactive sourcing. Lead cross-functional collaboration with Engineering, Design, Data Science, and go-to-market teams; define KPIs, pricing, packaging, and positioning; conduct user research; analyze metrics; build AI-powered experiences; and optimize the two-sided marketplace to improve employer outcomes and business growth.

Lead the strategy, architecture, and production delivery of large-scale machine learning systems for recommendations, matching, ranking, retrieval, and interaction prediction. Own the full model lifecycle from research and feature engineering through distributed training, experimentation, evaluation, and latency optimization. Mentor machine learning engineers and data scientists, establish organizational best practices, and partner with engineering and product leadership on the ML roadmap.

Lead design, development, and deployment of advanced machine learning models and infrastructure. Own architecture, data pipelines, experimentation, validation, and team technical leadership to drive AI-driven product features and business value.

Senior Software Engineers will build data processing pipelines and deploy cloud technologies, focusing on big data and machine learning infrastructure. They are expected to write and deploy efficient code within a Kubernetes environment.

The role involves designing and maintaining machine learning models, analyzing data, and optimizing algorithms to solve business problems.

Design and develop scalable user-facing web applications; improve engineering practices and collaborate with technical and non-technical stakeholders; engage with cross-functional teams.