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Mastercard
Mastercard
FinanceFintech
Mastercard is a global fintech and financial services company that powers electronic payments and commerce through its worldwide network. Its products span payment processing, digital and data services, fraud prevention, and security solutions for consumers, financial institutions, merchants, governments, and businesses. The company hires across a broad range of functions and focuses on innovation, sustainability, and inclusive economic growth.
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Senior Principal AI Engineer, AI Infrastructure — Mastercard, San Francisco Onsite

Lead the architecture of Mastercard’s secure, scalable AI infrastructure. Build HPC, GPU, Kubernetes, and hybrid-cloud platforms for production LLM workloads.

USUnited StatesCACaliforniaFLFloridaMAMassachusettsMOMissouriNYNew YorkWAWashington
$254,000 – $407,000 / year
On-siteFull-timeSeniorEnglish RequiredAI EngineerMachine Learning Engineer
CloudDistributed SystemsKubernetes

Description

  • Set the technical direction, architecture, and engineering standards for enterprise AI infrastructure and platforms
  • Guide the design and evolution of HPC, GPU-accelerated compute, rack-scale systems, private and hybrid cloud, Kubernetes, high-performance networking, storage, and AI platform services
  • Architect infrastructure for LLM training and inference, model serving, machine learning workloads, agentic AI orchestration, and emerging AI capabilities
  • Address complex infrastructure, performance, and scalability issues through architecture, prototyping, performance engineering, and hands-on troubleshooting
  • Define engineering practices for reliability, resilience, observability, automation, capacity planning, security, and operational readiness
  • Build security, privacy, Responsible AI, governance, compliance, and auditability into AI infrastructure from the outset
  • Assess emerging AI, HPC, GPU, networking, storage, and infrastructure technologies and help shape enterprise architecture and platform roadmaps
  • Direct complex cross-functional technical programs and mentor engineers through architecture reviews, engineering standards, reference designs, and knowledge sharing
  • Partner with AI Engineers, Data Scientists, Platform Engineers, Security, Architecture, and Product teams

Requirements

  • Background in AI engineering, high-performance computing, platform engineering, infrastructure engineering, distributed systems, cloud technology, or a related field
  • Demonstrated success architecting and operating secure, mission-critical platforms at enterprise scale
  • Advanced expertise in HPC, GPU and accelerated computing, rack-scale systems, Kubernetes, private and hybrid cloud, high-speed networking, storage, and infrastructure automation
  • Experience enabling LLM training and inference, machine learning models, large language models, agentic AI, and production AI platforms
  • Strong command of distributed systems, SRE, observability, resilience, security, governance, compliance, and production operations
  • Ability to lead complex architecture and engineering programs through technical depth, influence, and cross-functional partnership
  • Excellent communication and mentoring abilities, including engagement with senior stakeholders and development of engineering teams
  • Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related discipline
  • Comply with Mastercard’s security policies and practices
  • Protect the confidentiality and integrity of accessed information
  • Report suspected information security violations or breaches
  • Complete required periodic security training

Benefits

  • Annual bonus or commissions may be offered depending on the role
  • Medical, prescription drug, dental, vision, disability, and life insurance coverage
  • Flexible spending and health savings accounts
  • 16 weeks of new parent leave
  • Up to 20 days of bereavement leave
  • 80 hours of Paid Sick and Safe Time
  • 25 days of vacation
  • 5 personal days
  • 10 paid U.S. observed holidays each year
  • 401(k) with a best-in-class company match
  • Deferred compensation for eligible roles
  • Fitness reimbursement or access to on-site fitness facilities
  • Tuition reimbursement eligibility

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