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Posted 13 mo agoFirst seen 3 h ago
Senior Machine Learning Engineer
Posted by SeatGeek on 12 September 2025, 418 days ago. Still on their Greenhouse board when we checked 3 min ago.
What the posting is about
Design and build machine learning systems at scale for ticketing industry. Collaborate with cross-functional teams to translate research into production-ready systems. Solve complex technical challenges and drive business value.
Your experience, ready for this role
Answer a few questions about your real work. Review the additions and download your CV.
Read out of the posting
Levelsenior
Experience asked4+ years
EmploymentFull time
LocationNew York, New York
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot extracted, check the posting
Posted2025-09-12
Found viagreenhouse, direct from their system
We saw it 14 months after it went up.
The posting, as the company wrote it
SeatGeek believes live events are powerful experiences that unite humans. With our technological savvy and fan-first attitude we’re simplifying and modernizing the ticketing industry.
SeatGeek is a technology innovator on a mission to disrupt the $300 billion ticketing industry. We have the product, vision, and team to make life better for performers, venues, and fans, and build a generational consumer brand in the process. All we’re missing is you.
You will join a group that bridges the gap between research and production-ready ML systems. Your work will directly impact how millions of fans discover and purchase tickets, how we optimize pricing and inventory, how we personalize the SeatGeek experience, and how we prevent fraud across our marketplace. You will design and build ML infrastructure and services that operate at scale, turning complex algorithms into reliable, fast, and maintainable systems that drive business value.
What you'll do
Design, build, and deploy machine learning models and systems that operate reliably at scale in production
Build and maintain ML infrastructure including feature stores, model serving platforms, and real-time inference pipelines
Embed on a product engineering team and collaborate closely with data scientists, PMs ,and Software Engineers to translate research and experimental models into production-ready systems
Solve complex technical challenges unique to the ticketing industry, including real-time pricing optimization, demand forecasting, and fraud detection
Develop automated ML pipelines for training, validation, deployment, and monitoring using MLOps best practices
Work across team and discipline boundaries to evangelize ML capabilities and build them into SeatGeek's core product offerings
What you have
Experience building and deploying machine learning systems in production environments. We'll be interested in hearing about the systems you've built, the scale you've operated at, and the business impact you've driven
4+ years of experience in software engineering with at least 2+ years focused on machine learning systems and MLOps
Strong programming skills in Python and experience with ML frameworks like scikit-learn, TensorFlow, PyTorch, or similar
Experience with cloud platforms and containerization technologies
Understanding of both batch and real-time ML systems, including experience with model serving, A/B testing, and performance monitoring
Passion for software craftsmanship and product. You have well-considered opinions about how systems should be built, and hold yourself and your code to a high standard
A product mindset. You think beyond the model accuracy, about user experience, business impact, system reliability, and what makes a great product tick
Commitment to your teammates. You enjoy working with a diverse group of people with different experiences and take pride in mentoring and learning from others
Our stack
You do not need experience with all of these, but we thought you might be curious. What we care about is your experience, skills, and approach to problem solving. Tools can be learned.
Languages + Frameworks: Python + FastAPI, Go, C# + .NET Core
Datastores: Postgres, MemcachedRedis, Elasticsearch
Cloud: AWS (SageMaker, Redshift, ECS), Airflow for orchestration
Version control: Gitlab
AI Tooling: Cursor, Github Copliot, Claude Code
Observability: Datadog
Perks
Equity stake
Discretionary annual bonus
Flexible work environment, allowing you to work as many days a week in the office as you’d like or 100% remotely
A WFH stipend to support your home office setup
Unlimited PTO
Up to 16 weeks of fully-paid family leave
401(k) matching
Student loan matching program
Health, vision, dental, and life insurance
Up to $25k towards family building, reproductive health services and Gender-affirming care
$500 per year for wellness expenses
Subscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical
$360 per quarter to spend on tickets to live events
Annual subscription to Spotify, Apple Music, or Amazon music
The salary range for this role is $145,000 - $209,000 USD. This role is equity eligible. In addition, you may receive a discretionary annual bonus based on individual and company performance. Actual compensation packages within that range are based on a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, certifications, and specific location.
SeatGeek is committed to providing equal employment opportunities to all employees and applicants for employment regardless of race, color, religion, creed, age, national origin or ancestry, ethnicity, sex, sexual orientation, gender identity or expression, disability, military or veteran status, or any other category protected by federal, state, or local law. As an equal opportunities employer, we recognize that diversity is a positive attribute and we welcome the differences and benefits that a diverse culture brings. Come join us!
To review our candidate privacy notice, click here .
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