Role Description The Platform team is part of the Marketplace engineering: we provide specialized business platforms supporting Marketplace ML and Optimization products. We own and host core ML models used throughout the Marketplace; we automate all parts of the model life cycle, such as feature engineering, training workflows and inference services; we are working on next-generation Marketplace Simulation system capable to run high-fidelity virtual experiments; we also streamline diverse Marketplace Experimentation practices with the goal of providing unified user-friendly Experimentation platform. - Implement and scale the core economic engine for Waymo's ride-hailing commercial services. - Work on novel experimentation, simulation and analysis infrastructure supporting Marketplace product data science. Qualifications - BS degree in Computer Science or equivalent practical experience. - 4+ years of experience programming in backend coding languages such as Java or C++. - Experience in building backend platforms supporting multiple product use-cases/services. - Experience working with product data science teams and developing code to automate ML/Optimization product launches. Requirements - MS in Computer Science, or equivalent practical experience. - Experience building and deploying high-fidelity simulation systems running ML/Optimization production code. - Experience developing and configuring Experimentation services running concurrent A/B or Switchback experiments. - Experience working at another Ride hailing or Marketplace company. - Coursework background in experiment design or simulation systems. Benefits - Waymo employees are eligible to participate in Waymo’s discretionary annual bonus program. - Equity incentive plan. - Generous Company benefits program, subject to eligibility requirements. Salary Range The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Salary Range: $175,000 — $215,000 USD

• Lead the engineering organization for data and AI/ML platform • Develop petabyte-scale infrastructure for data and AI • Drive cross-functional alignment and strategic platform decisions • Set product vision and roadmap for platform areas • Manage engineering team and grow organization

Role Description We are looking for a technically sharp and people-focused Platform Engineer to own, scale, and optimize our internal Salesforce platform. This role isn't just about administration — it's about architecting scalable, high-quality solutions that make the People team and the employees they support more effective every day. - You will be the primary technical owner of our People Salesforce org balancing KLTO (Keep Lights On) operations with strategic platform improvements. - Work closely with People Operations, People Solutions, GTMS, Corporate Technology, and vendor teams to ensure our Salesforce platform is well-governed, deeply integrated, and continuously improving. - Bridge the gap between HR strategy and technical execution, ensuring our Salesforce environment is secure, highly automated, and seamlessly integrated with the rest of our tech stack (e.g., Slack). Responsibilities - Design, build, and maintain scalable configurations and customisations within the Salesforce platform. - Build robust, maintainable declarative solutions — including Advanced Flows and Approval Processes. - Own and optimize data pipelines and API integrations between Salesforce and core People systems (e.g. Workday). - Maintain strict data privacy standards by managing profiles, permission sets, sharing rules, and field-level security for sensitive HR data. - Own the deployment pipeline to ensure smooth, well-tested releases of new HR features. - Monitor app health and performance across critical People workflows, triage incidents with urgency and rigour. - Build complex reports, dashboards, and CRM Analytics to help the People team track key metrics. - Work alongside the broader People Solutions team to translate business requirements into a prioritised Salesforce product roadmap. - Partner with Global People Operations, People partners, wider People team, Corporate Technology, and other stakeholders to translate complex business needs into scalable technical requirements. Qualifications - 5+ years of hands-on experience as a Salesforce Engineer, Platform Specialist, or Advanced Administrator. - Deep knowledge of HR Service, Service Cloud (Case Management, Knowledge Base, Omni-Channel) and Experience Cloud (Employee Portals). - Proficient with Salesforce Flow, data migration tools (Data Loader), and a solid understanding of relational databases. - Proven experience handling highly confidential data with strict governance and security controls. - Salesforce Certified Administrator and Salesforce Certified Platform App Builder are highly preferred. - Strong interpersonal skills with the ability to set clear expectations with senior stakeholders. - Ability to lead cross-functional projects, navigating ambiguity and high-pressure timelines. - Bachelor’s degree or equivalent practical experience. Preferred qualifications - Experience with Salesforce Apex, Lightning Web Components (LWC). - Familiarity with HRIS platforms (e.g., Workday, Greenhouse, ADP) and integration tools (e.g., MuleSoft, Workato, Zapier). - Experience working in an Agile/Scrum environment using tools like Jira. - Familiarity with HR service delivery models, case management workflows, and the broader People/HR technology landscape. - You are a "low-ego, high-talent" individual who loves adding organization to chaos.

Role Description We are hiring a Senior Platform Engineer to lead security tooling and enablement within Platform Engineering for our global SaaS environment. This role focuses on building the platforms, automation, and guardrails that help engineering teams adopt security requirements in practical, scalable ways across the software development lifecycle. You will work at the intersection of Security, Platform Engineering, and development teams. In our model, the Security team defines policies, standards, and best practices, and Platform Engineering enables and enforces them through engineering solutions. This is a senior individual contributor role for an engineer who can lead proofs of concept, drive initiatives with limited guidance, and turn complex problems into clear, executable solutions. What you will do: - Lead security tooling across application security, dependency and supply chain security, artifact and container security, cloud security posture, and policy-driven workflows. - Build, integrate, and operate tools such as GitHub Advanced Security, JFrog Xray, Prisma, Black Duck, Checkmarx, and similar platforms. - Design automation for vulnerability detection, dependency hygiene, patch planning, remediation tracking, and governed security workflows. - Partner with Security and Engineering to turn defined policies and best practices into practical controls, delivery pipeline guardrails, and developer-friendly workflows. - Improve the developer experience of security tooling by reducing noise, improving remediation clarity, and helping teams move faster without weakening security controls. - Drive security-focused initiatives and OKR efforts by defining technical approaches, breaking down work, and leading execution. - Support the ongoing health and improvement of security tooling, including internally built or AI-assisted security automation where appropriate. - Work with operational teams to support secure adoption of AI-enabled engineering tools and build controls around their use where needed. Qualifications - 5+ years of experience in security engineering, platform engineering, development operations, site reliability engineering, or software engineering in production environments. - Strong programming or scripting skills in Go, Python, Bash, or similar languages. - Hands-on experience with security tooling and practices across areas such as code scanning, dynamic testing, software composition analysis, secret scanning, container or image scanning, artifact security, cloud security posture management, and policy enforcement. - Experience with or exposure to tools such as GitHub Advanced Security, JFrog Xray, Prisma, Black Duck, Checkmarx, Dependabot, Renovate, or similar security and dependency management platforms. - Strong understanding of vulnerability management, dependency management, and security controls within software delivery and developer workflows. - Familiarity with Kubernetes, containers, cloud platforms, Git-based workflows, and infrastructure as code concepts. - Ability to lead technical initiatives, run proofs of concept, and deliver solutions from ambiguous requirements. - Strong collaboration and communication skills, with the ability to translate security needs into practical engineering solutions. Requirements - Experience using AI-assisted tools to improve engineering productivity, security workflows, and developer experience. - Familiarity with AI-assisted coding tools such as GitHub Copilot or Cursor for work such as code review, documentation, and test generation. - Experience applying AI to security use cases such as log analysis, threat investigation, remediation support, or security documentation. - Familiarity with large language model APIs, agent-based workflows, or internally built AI tooling, along with the ability to evaluate and enable these tools responsibly within engineering environments. - Understanding of security considerations for AI tools, including data leakage, prompt injection, shadow AI, and compliance with enterprise AI policies. Preferred Skills - Exposure to compliance-driven environments such as SOC 2 or similar frameworks. - Experience supporting AI-assisted or internally built security automation. - Familiarity with modern software delivery environments where security tooling must balance risk reduction with engineering velocity.