SeatGeek Logo

SeatGeek

Senior Machine Learning Engineer

Reposted 13 Hours Ago
Remote
Hiring Remotely in United States
145K-200K Annually
Senior level
Remote
Hiring Remotely in United States
145K-200K Annually
Senior level
As a Senior Machine Learning Engineer, you will design, build, and deploy ML systems at scale, collaborating closely with teams to optimize ticket pricing, demand forecasting, and fraud detection while maintaining high standards in software development.
The summary above was generated by AI
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
  • 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 program
  • Student loan support resources
  • Health, vision, dental, and life insurance
  • Up to $25k towards family building and reproductive health services
  • Gender-affirming care support program
  • $500 per year for wellness expenses
  • Subscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical
  • $120 per month 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-$200,000 USD. 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

Top Skills

.Net Core
AWS
C#
Datadog
Ecs
Elasticsearch
Fastapi
Gitlab
Go
Memcached
Postgres
Python
PyTorch
Redis
Redshift
Sagemaker
Scikit-Learn
TensorFlow

Similar Jobs

4 Days Ago
Remote or Hybrid
United States
119K-222K Annually
Senior level
119K-222K Annually
Senior level
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Design and build a machine learning platform, deploy ML models, collaborate across teams, and establish monitoring standards for AI solutions.
Top Skills: AIAmazon BedrockAmazon SagemakerAWSDockerFeastMicroservicesMlRestful Apis
5 Days Ago
In-Office or Remote
Select, KY, USA
213K-288K Annually
Senior level
213K-288K Annually
Senior level
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
The Senior Machine Learning Engineer will design and implement ML models to enhance security, detect threats, and protect user trust in collaboration with various teams.
Top Skills: Apache KafkaAws KinesisData ScienceDatabricksGoogle Pub/SubJavaMachine LearningPythonScalaSpark
13 Days Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
135K-228K Annually
Senior level
135K-228K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.
Top Skills: C++Computer VisionDeep Learning FrameworksEdge AiPython

What you need to know about the Boston Tech Scene

Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.

Key Facts About Boston Tech

  • Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
  • Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
  • Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
  • Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account