Description review
Senior Machine Learning Engineer
SeatGeek · USA · back to the listing
HR standards
66/100
needs work
Title ↔ description
89/100
strong
Reads as
Machine Learning Engineer
100% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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What the listing never says
- 34 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
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
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