Jobs at ZipRecruiter

Manage and grow enterprise accounts through renewals, upsells, client support, campaign optimization, performance analysis, product demonstrations, and relationship building. Partner with sales and customer success teams, onboard and train clients, present analytics, optimize advertising campaigns, and identify opportunities to increase revenue and retention. The role requires at least 25% travel, including approximately nine client visits per quarter.

Staff Software Engineer for the Job Seeker Apps team, building user-facing interfaces, backend systems, proactive communications, and AI assistant integrations. Responsibilities include end-to-end systems engineering, collaboration with Product and Decision Science, technical leadership and mentorship, impact measurement, and architecting safe, scalable agentic integrations. The role requires extensive software development experience and may involve ReactJS, TypeScript, data lake technologies, and distributed data processing frameworks.

Lead a team of five engineers responsible for modernizing job ingestion pipelines, data stores, data access, data quality, and fraud detection systems. Partner with product managers, data scientists, and engineering stakeholders to prioritize scalable, real-time data initiatives. Improve the handling of messy user-generated and third-party data while ensuring performance, maintainability, security, and personalization capabilities across ZipRecruiter’s job marketplace.

Lead the Machine Learning Ranking team, managing data scientists and ML engineers while driving career development, technical quality, and product outcomes. Partner with Product Management and Decision Science to define roadmaps, metrics, and marketplace experiments. Oversee machine-learning pipeline development, model deployment, and performance monitoring. Provide technical guidance on ML and AI applications, evaluate engineering work, and promote scalable, reproducible practices across the team.

Designs, builds, deploys, and maintains scalable data pipelines, data lake systems, batch and streaming processing, MLOps frameworks, data documentation tooling, and an agentic data exploration platform. The role supports customer-facing products and enables engineering teams through reliable infrastructure, observability, data discovery, and AI capabilities.

Build and operate scalable batch and streaming data pipelines, data lake infrastructure, MLOps frameworks, data documentation systems, and an AI-assisted data exploration tool. The role focuses on reliable data ingestion, large-scale processing, workflow orchestration, observability, and infrastructure supporting customer-facing products and machine learning development.

Leads enterprise sales enablement for Direct Sales, translating product capabilities and market insights into sales plays, launch readiness, messaging, training, content, and customer insights. Partners with Sales, Marketing, Product, Customer Success, and Revenue Operations to improve pipeline conversion, product adoption, account expansion, and sales effectiveness. Measures program impact through adoption, pipeline, penetration, and revenue metrics while building scalable workflows and field feedback loops.

Lead SMB revenue operations strategy and execution, manage and coach a team of analysts, prioritize and deliver cross-functional GTM projects, optimize processes and systems, and rapidly resolve operational issues to enable scalable revenue growth.

Build scalable data processing and exploration pipelines, ML infrastructure, and cloud-based applications. Write, test, instrument, and deploy software in Kubernetes environments while contributing to distributed systems and data-driven products. The role focuses on Python, big data technologies, containerization, and systems supporting marketplace intelligence.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

The role involves building data processing pipelines, deploying cloud technologies, and writing code in a Kubernetes environment, focusing on big data technologies.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

Lead a Big Data Engineering team to deliver production-grade ETL and data pipelines at scale. Own team execution, code quality, morale, and roadmap execution with product managers. Remove roadblocks, coach and develop engineers, promote engineering best practices, and enable data-driven and AI-powered product features (personalization, recommendations, search, ranking, matching).

Lead a Machine Learning engineering team owning mission, execution, morale, and code quality. Partner with product to deliver roadmap, remove roadblocks, improve processes, coach and grow engineers, and drive development, deployment, and innovation of ML models for recommender, search, and matching systems.

Lead one or more engineering teams owning mission, execution, code quality, and morale. Partner with product managers on roadmaps, remove roadblocks, improve processes, coach and grow engineers, and drive innovation while delivering high-traffic full-stack or data applications at scale.

Design and implement scalable web applications while raising engineering innovation standards. Communicate technical solutions to diverse stakeholders and collaborate with teams to deliver products.