Staff Machine Learning Infrastructure Engineer

StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we’re here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world.

About the Opportunity

We're seeking an accomplished Staff Machine Learning Infrastructure Engineer to join StubHub's Data Engineering & Analytics team as a high-impact individual contributor focused on machine learning infrastructure and real-time inference systems. You'll architect and build the foundational ML platforms that power recommendation systems, pricing optimization, and personalization across StubHub's product. 

As a Staff-level IC, you'll operate as a technical force multiplier, setting technical direction for ML infrastructure across the organization. You'll lead through influence rather than management, advocating for long-term technical progress while balancing organizational needs. Your work will span strategic initiatives measured in months and years, focusing on high-leverage technical decisions that enable entire teams to be more effective. 

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Los Angeles, CA    Strategic Need We have increasing needs to scale our machine learning capabilities to power personalized experiences, dynamic pricing, and intelligent recommendations across our platform. Our current ML infrastructure requires modernization to support real-time inference at scale, improve feature engineering workflows, and enable faster model deployment and iteration cycles. Additionally, we need to create the foundational data model along with the corresponding data pipelines, and build shared tooling to ease the process of developing and operating high quality trustworthy data assets.    What You'll Do

As a Staff Enginner focused on ML Infrastructure, you'll work across four key dimensions: 

Setting Technical Direction 

• Architect ML infrastructure strategy that aligns technical approaches across Data Science, ML Engineering, and Platform teams 
• Drive consensus on technical vision for feature stores, inference services, and model lifecycle management 
• Advocate for long-term technical progress while balancing immediate organizational needs 
• Establish architectural patterns that become standards across StubHub's ML ecosystem 

Core ML Infrastructure & Exploration 

• Prototype and investigate ambiguous, high-impact ML infrastructure problems 
• Build production-grade inference services with sub-100ms latency, intelligent caching, and 99.9% uptime SLAs 
• Design model lifecycle management systems including versioning, A/B testing, rollback capabilities, and performance monitoring 
• Modernize recommendation systems from legacy SQS-based architecture to scalable, real-time streaming solutions 
• Explore innovative solutions outside standard approaches for complex ML infrastructure challenges 

Technical Leadership & Mentorship 

• Provide engineering perspective in high-level organizational discussions about ML strategy 
• Mentor engineers across the platform, actively sponsoring promising team members 
• Inject technical context