StubHub
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
into critical decision-making processes Lead complex technical initiatives
spanning multiple teams and quarters Being the "Glue"
Connect different team efforts
to ensure ML infrastructure initiatives succeed Handle behind-the-scenes work
that keeps critical ML projects moving forward Expedite high-priority ML infrastructure needs
across the organization Ensure important strategic work
gets completed even when it spans team boundaries What You've Done
8+ years
of relevant software or data engineering development experience in a fast-paced, high growth environment 3+ years
of experience with machine learning infrastructure, MLOps, or ML platform engineering Proven track record
of setting technical direction and leading complex, multi-team initiatives Strong programming and analytical ability
with expertise in Python, Scala, or Java, and infrastructure-as-code Experience with feature store services
and how they interoperate between batch and live inference systems Experience with live inference services
including caching, SLAs, and performance optimization for production ML workloads Experience with model lifecycle management
including versioning, A/B testing, and rollback capabilities Experience with streaming systems
(Spark, Kafka) and how they relate to overarching ML platform architecture Experience with cloud-based ML platforms
such as AWS SageMaker, Google Vertex AI, or Azure ML Experience mentoring engineers
and establishing technical best practices across teams Staff-Level Capabilities
Technical leadership through influence
rather than formal management authority Strategic thinking
with ability to balance long-term technical vision with immediate organizational needs Cross-functional collaboration
skills to work effectively with Data Science, Product, and Engineering teams Communication skills
to inject technical context into high-level organizational discussions Problem-solving approach
for ambiguous, high-impact technical challenges Mentorship and sponsorship
experience growing junior and mid-level engineers Nice to Have
Experience with real-time recommendation systems
and personalization platforms at scale Knowledge of ML model serving frameworks
(TensorFlow Serving, TorchServe, Seldon, etc.) Experience with A/B testing frameworks
and experimentation platforms Experience with distributed computing frameworks
(Ray, Dask, etc.) Knowledge of ML security and privacy considerations Track record of technical writing
or speaking at conferences about ML infrastructure What We Offer:
Accelerated Growth Environment:
Immerse yourself in an environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale. Top Tier Compensation Package:
Enjoy a rewarding compensation package that includes enticing stock incentives, aligning with our commitment to recognizing and valuing your contributions. Flexible Time Off:
Embrace a healthy work-life balance with unlimited Flex Time Off, providing you the flexibility to manage your schedule and recharge as needed. Comprehensive Benefits Package:
Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.
The anticipated gross base pay range is below for this role. Actual compensation will vary depending on factors such as a candidate's qualifications, skills, experience, and competencies. Base annual salary is one component of StubHub's total compensation and competitive benefits package, which includes equity, 401(k), paid time off, paid parental leave, and comprehensive health benefits.
Salary Range
$300,000-$350,000 USD
About Us
StubHub is the world's leading marketplace to buy and sell tickets to any live event, anywhere. Through StubHub in North America and viagogo, our international platform, we service customers in 195 countries in 33 languages and 49 available currencies. With more than 300 million tickets available annually on our platform to events around the worldfrom sports to music, comedy to dance, festivals to theaterStubHub offers the safest, most convenient way to buy or sell tickets to the most memorable live experiences. Come join our team for a front-row seat to the action.
For California Residents: California Job Applicant Privacy Notice found here
We are an equal opportunity employer and value diversity on our team. We do not discriminate on the basis of race, color, religion, sex, national origin, gender, sexual orientation, age, disability, veteran status, or any other legally protected status.
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
into critical decision-making processes Lead complex technical initiatives
spanning multiple teams and quarters Being the "Glue"
Connect different team efforts
to ensure ML infrastructure initiatives succeed Handle behind-the-scenes work
that keeps critical ML projects moving forward Expedite high-priority ML infrastructure needs
across the organization Ensure important strategic work
gets completed even when it spans team boundaries What You've Done
8+ years
of relevant software or data engineering development experience in a fast-paced, high growth environment 3+ years
of experience with machine learning infrastructure, MLOps, or ML platform engineering Proven track record
of setting technical direction and leading complex, multi-team initiatives Strong programming and analytical ability
with expertise in Python, Scala, or Java, and infrastructure-as-code Experience with feature store services
and how they interoperate between batch and live inference systems Experience with live inference services
including caching, SLAs, and performance optimization for production ML workloads Experience with model lifecycle management
including versioning, A/B testing, and rollback capabilities Experience with streaming systems
(Spark, Kafka) and how they relate to overarching ML platform architecture Experience with cloud-based ML platforms
such as AWS SageMaker, Google Vertex AI, or Azure ML Experience mentoring engineers
and establishing technical best practices across teams Staff-Level Capabilities
Technical leadership through influence
rather than formal management authority Strategic thinking
with ability to balance long-term technical vision with immediate organizational needs Cross-functional collaboration
skills to work effectively with Data Science, Product, and Engineering teams Communication skills
to inject technical context into high-level organizational discussions Problem-solving approach
for ambiguous, high-impact technical challenges Mentorship and sponsorship
experience growing junior and mid-level engineers Nice to Have
Experience with real-time recommendation systems
and personalization platforms at scale Knowledge of ML model serving frameworks
(TensorFlow Serving, TorchServe, Seldon, etc.) Experience with A/B testing frameworks
and experimentation platforms Experience with distributed computing frameworks
(Ray, Dask, etc.) Knowledge of ML security and privacy considerations Track record of technical writing
or speaking at conferences about ML infrastructure What We Offer:
Accelerated Growth Environment:
Immerse yourself in an environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale. Top Tier Compensation Package:
Enjoy a rewarding compensation package that includes enticing stock incentives, aligning with our commitment to recognizing and valuing your contributions. Flexible Time Off:
Embrace a healthy work-life balance with unlimited Flex Time Off, providing you the flexibility to manage your schedule and recharge as needed. Comprehensive Benefits Package:
Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.
The anticipated gross base pay range is below for this role. Actual compensation will vary depending on factors such as a candidate's qualifications, skills, experience, and competencies. Base annual salary is one component of StubHub's total compensation and competitive benefits package, which includes equity, 401(k), paid time off, paid parental leave, and comprehensive health benefits.
Salary Range
$300,000-$350,000 USD
About Us
StubHub is the world's leading marketplace to buy and sell tickets to any live event, anywhere. Through StubHub in North America and viagogo, our international platform, we service customers in 195 countries in 33 languages and 49 available currencies. With more than 300 million tickets available annually on our platform to events around the worldfrom sports to music, comedy to dance, festivals to theaterStubHub offers the safest, most convenient way to buy or sell tickets to the most memorable live experiences. Come join our team for a front-row seat to the action.
For California Residents: California Job Applicant Privacy Notice found here
We are an equal opportunity employer and value diversity on our team. We do not discriminate on the basis of race, color, religion, sex, national origin, gender, sexual orientation, age, disability, veteran status, or any other legally protected status.