Senior Machine Learning Engineer

SeatGeek is a technology innovator on a mission to disrupt the $300 billion ticketing industry. You will join a group that bridges the gap between research and production-ready ML systems, designing and building ML infrastructure that impacts how millions of fans discover and purchase tickets.

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

Requirements:

• 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