Join SeatGeek, a Technology Innovator Disrupting the 0 Billion Ticketing Industry
SeatGeek is redefining the ticketing landscape by simplifying and modernizing the industry. We’re on a mission to make live events more accessible and enjoyable for everyone. If you’re ready to revolutionize the way people find and purchase tickets, we want to hear from you.
What You’ll Do
As a member of the team that bridges the gap between research and production-ready ML systems, you’ll be responsible for designing and building ML infrastructure and systems that operate at scale. Your work will impact how millions of fans discover and purchase tickets, optimize pricing and inventory, personalize the SeatGeek experience, and prevent fraud.
- 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 Bring
- Experience building and deploying machine learning systems in production environments
- 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 Copilot, 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 k towards family building, reproductive health services and gender-affirming care
- 0 per year for wellness expenses
- Subscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical
- 0 per quarter to spend on tickets to live events
- Annual subscription to Spotify, Apple Music, or Amazon Music
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