[Remote] Senior Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. SeatGeek is a technology innovator on a mission to disrupt the $300 billion ticketing industry. They are seeking a Senior Machine Learning Engineer to design and build machine learning infrastructure and services that operate at scale, impacting how millions of fans discover and purchase tickets, optimize pricing, and prevent fraud.

Responsibilities

• 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

Skills

• 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
• A product mindset
• Commitment to your teammates
• 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

Benefits

• 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
• $120 per month to spend on tickets to live events
• Annual subscription to Spotify, Apple Music, or Amazon music

Company Overview

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