Director, AI Engineering (Redwood City)

Who are we?Equinix is the world’s digital infrastructure company, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective.Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.Job SummaryWe are seeking a Director of AI Engineering to lead and scale a high-performing Machine Learning Engineering (MLE) organization. This leader will be responsible for building production-grade AI/ML systems that power next-generation generative and predictive capabilities across the enterprise. The role combines deep technical leadership, organizational scale, and strong business alignment to translate AI innovation into measurable impact.Reporting to Yang Song within Digital and Innovation Office, this role will work closely with the Data & Engineering team around technology and development. This is a hands-on technical leadership role responsible for building and scaling production-grade AI systems.This role is critical to transforming AI from experimentation into a scalable, enterprise capability. You will define how AI is built, deployed, and leveraged across the organization—unlocking faster decisions, smarter automation, and sustained competitive advantage.ResponsibilitiesLead and Scale the MLE OrganizationBuild, lead, and mentor a global team of Machine Learning Engineers and technical leadersEstablish a high-performance engineering culture focused on quality, velocity, and accountabilityDrive hiring, onboarding, and career development for MLE talent across regionsDeliver Production-Grade AI/ML SystemsOwn end-to-end delivery of ML platforms, pipelines, and services (training, inference, monitoring)Operationalize models into scalable, reliable, and secure production systemsPartner with Data Science and Product to move from experimentation to deploymentDefine AI Engineering Strategy & ArchitectureSet the vision for ML platform architecture, MLOps, and GenAI enablementStandardize tools, frameworks, and best practices for model development and deploymentEnsure systems are built for scale, performance, and cost efficiencyDrive Generative AI and Advanced AnalyticsLead development of GenAI capabilities (LLMs, RAG, copilots, automation workflows)Enable reusable AI services and APIs to accelerate use case deliveryStay ahead of industry trends and translate them into enterprise-ready capabilitiesCross-Functional Leadership & Stakeholder AlignmentPartner with Product, Data, Engineering, and Business leaders to prioritize high-impact use casesCommunicate strategy, progress, and outcomes to executive stakeholdersAlign AI initiatives with business goals, including revenue growth, efficiency, and customer experienceGovernance, Risk, and Responsible AIEstablish best practices for model governance, monitoring, and lifecycle managementEnsure compliance with security, privacy, and ethical AI standardsImplement guardrails for safe and responsible use of AI technologiesQualifications12+ years in software engineering, data engineering, or ML engineering5+ years leading large, distributed engineering teams (including managers of managers)Proven track record of delivering ML/AI systems at scale in production environmentsDeep knowledge of machine learning systems, MLOps, and cloud-native architecturesExperience with ML frameworks (e.g., TensorFlow, PyTorch) and data platformsStrong understanding of GenAI/LLMs, prompt engineering, and retrieval-augmented systemsFamiliarity with distributed systems, APIs, and microservices architectureStrong ability to translate business strategy into technical executionExperience driving large-scale transformation initiativesExcellent communication and stakeholder management skillsPreferred:Experience building enterprise AI platforms or internal AI productsBackground in both predictive ML and generative AI use casesExperience in global delivery models (e.g., US + India engineering hubs)Master’s or PhD in Computer Science, Engineering, or related fieldundefinedThe targeted pay range for this position in the following location is / locations are:United States - Redwood City Office GHQ : 269,000 - 403,000 USD / AnnualUnited States - Dallas Infomart Office DAI : 224,000 - 336,000 USD / AnnualCanada - Toronto Office TRO : 182,000 - 272,000 CAD / AnnualOur pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location.The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job-related skills, experience, and relevant education and/or training.The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position.Equinix BenefitsAs an employee, you become important to Equinix’s success. We ensure all your benefits are in line with our core values: competitive, inclusive, sustainable, connected and efficient. We keep them competitive within the current marketplace to ensure we’re providing you with the best package possible. So, wherever you are in your career and life, you’ll be able to enhance your experience and bring your whole self to work.Employee Assistance Program: An Employee Assistance program is available to all employees.
US Benefits: - Insurance: You may enroll in health, life, disability and voluntary plans that are designed for you and your eligible family members. - Retirement: You and Equinix may contribute to a retirement plan to help you plan for your financial future. - Paid Time Off (PTO) and Paid Holidays: You will receive an accrued amount of PTO each pay period along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to change and may be subject to specific plan or program terms.

Canada Core Benefits: - Insurance: You may enroll in healthcare coverage that is designed to complement the provincial healthcare system, along with life, disability and optional benefit plans that are designed for you and your eligible family members. - Retirement: You may also enroll in Equinix-sponsored retirement or savings plans: Defined Contribution Pension Plan (DCPP), Group Retirement Savings Plan (RRSP) and Tax-Free Savings Plan (TSFA). - Vacation and Paid Holidays: Equinix offers both vacation and personal time, along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to specific plan or program terms, and to change at Equinix discretion.
Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form. Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law. We use artificial intelligence in our hiring process. Learn more here.
This posting is a new position within our organization.
SummaryLocation: Redwood City; Toronto; Dallas Infomart Office DAIType: Full time