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Senior Machine Learning Engineer

Pay
Multiple pay statements — pay source
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
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!
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Work setting
Remote — work setting source
Listed location: Remote - United States
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Employment
Not stated

What you’ll work on

Full posting
  • Design, build and deploy ML models and systems that run reliably at scale

  • Build and maintain feature stores, model serving and real-time inference pipelines

  • Embed on a product team, turning research models into production systems

  • Solve ticketing problems like real-time pricing, demand forecasting and fraud detection

  • Develop automated ML pipelines for training, validation, deployment and monitoring

From the employer’s posting
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

Benefits in the posting

Full benefits wording
  • Equity stake
  • Discretionary annual bonus
  • 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
  • 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.

From the employer’s posting.

Apply at SeatGeek

Posting record

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Open 6 monthsWe first saw this posting 204 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Apr 14, 2026204 days ago
Recorded sightings
153
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 204

Up longer than most. Similar jobs usually come down between day 6 and day 70.

Well past SeatGeek’s usual: its jobs come down by about day 3.

From 4,459 similar postings that came down, and 5 of SeatGeek’s. Coming down is not always a hire.

SeatGeek is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down quickly
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • C#
  • Python
  • AWS
  • Datadog
  • Elasticsearch
  • Redshift
  • SageMaker
  • Airflow
  • FastAPI
  • PyTorch
  • scikit-learn
  • TensorFlow
  • Go
  • PostgreSQL
Where the posting names them
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
- 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
- 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
- Languages + Frameworks: Python + FastAPI, Go, C# + .NET Core - Datastores: Postgres, MemcachedRedis, Elasticsearch - Cloud: AWS (SageMaker, Redshift, ECS), Airflow for orchestration

Your next step

Complete your application on seatgeek.com. The employer’s form will show what is required.

Applying through Greenhouse

  • No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
  • Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.

Already applied? Track this application

Has SeatGeek posted this job before?

Yes. We’ve followed one other Senior Machine Learning Engineer job there since April 2026. It is still up.

  1. New YorkStill up after 205 days, first seen Apr 14
  2. This jobUp 205 days so far, first seen Apr 14

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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.

#LI-Remote
Source details

View original posting ↗

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Pay
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
More source context
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!
Location & working pattern

Remote - United States

To review our candidate privacy notice, click here. #LI-Remote
Work authorization

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