Senior Machine Learning Engineer
Posted 367 days ago, which is unusual. The employer's own board was still carrying it when we last read it, just now.
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 367d ago
The date the source published, not the day we noticed it (2025-09-12). Last seen at its source just now.
Is it remote?
Remote - United States
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$145k–209k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
greenhouse employer's own board first seen 33d ago · last seen just now
The listing
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.