Senior ML Engineer: Scale Real-Time AI (Remote)

The Briefed; Northern (KY); Hybrid; USD 145,000 - 209,000; Full time

Benefits offered by this job

Equity stake

Discretionary annual bonus

Flexible remote work

WFH stipend

Unlimited PTO

Family leave

401(k) matching

Student loan matching

Health insurance

Wellness stipend

Headspace subscription

Live events ticket stipend

Music subscription

Job summary

SeatGeek is seeking a seasoned ML engineer to design and deploy machine learning systems that operate at scale in production, shaping pricing, inventory, and fraud prevention for millions of fans.

You will build ML infrastructure and pipelines, collaborate with data scientists, PMs, and software engineers to translate research into reliable, production-ready systems, and continuously improve model serving and monitoring in a dynamic marketplace.

Qualifications

• Experience deploying ML systems in production with measurable impact.
• 4+ years software eng with at least 2+ years ML/MLOps.
• Strong Python skills and ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Experience with cloud platforms and containerization.
• Understanding of batch and real-time ML, model serving, A/B testing, monitoring.

Responsibilities

• Design, build, and deploy ML models and systems at scale.
• Develop ML infrastructure: feature stores, model serving, real-time pipelines.
• Collaborate with data scientists, PMs, and engineers to productionize research.
• Address real-time pricing, demand forecasting, and fraud detection challenges.
• Build automated ML pipelines for training, validation, deployment, and monitoring.
• Advocate ML capabilities across SeatGeek products.

Skills

Production ML systems

Python

ML frameworks

Cloud platforms

Containerization

MLOps

Model serving

A/B testing

Performance monitoring

Team collaboration

Tools

FastAPI

Go

C# + .NET Core

Postgres

Redis

Memcached

Elasticsearch

AWS

SageMaker

Redshift

ECS

Airflow

Gitlab

Datadog

Cursor

GitHub Copilot

Job description

SeatGeek is seeking a seasoned ML engineer to design and deploy machine learning systems that operate at scale in production, shaping pricing, inventory, and fraud prevention for millions of fans.

You will build ML infrastructure and pipelines, collaborate with data scientists, PMs, and software engineers to translate research into reliable, production-ready systems, and continuously improve model serving and monitoring in a dynamic marketplace.