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# Machine Learning Engineer II

- **Company:** TRENT HOEK OUTDOORS LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $145,000.0 - $209,000.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, A/B Testing, Artificial Intelligence, Airflow, Amazon Web Services, C Sharp (Programming Language), Cloud Computing, Computer Programming, Data Stores, Cursor, Elasticsearch, Fraud Prevention and Detection, Python (Programming Language), PostgreSQL, Machine Learning, Memcached, Redis, Tensorflow, Software Engineering, Datadog, Feature Store, .NET Core, GitHub Copilot, Pytorch, Claude Code, Model Validation, Reliability of Systems, Gitlab, Fastapi, Containerization, Scikit Learn, Performance Monitor, Machine Learning Operations, Software Version Control, Service Stack, Golang
- **Published:** October 29, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pvbl3dx5hq

## About the Role

* Experience building and deploying machine learning systems in production environments, with the ability to discuss system scale and business impact.
 * At least 4 years of software engineering experience, including 2 or more years focused on machine learning systems and MLOps.
 * Strong programming skills in Python and experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or similar tools.
 * Experience with cloud platforms and containerization technologies.
 * Understanding of batch and real-time machine learning systems, including model serving, A/B testing, and performance monitoring.
 * A strong commitment to software craftsmanship, maintainable code, and high engineering standards.
 * A product-focused mindset that considers user experience, business impact, system reliability, and model performance.
 * A collaborative approach to working with people from diverse backgrounds, including a willingness to mentor teammates and learn from others., SeatGeek's technology stack includes the following tools and platforms. Experience with every tool is not required; the company values relevant skills, experience, and problem-solving ability.
 * Languages and frameworks: Python, FastAPI, Go, C#, and .NET Core
 * Datastores: PostgreSQL, Memcached, Redis, and Elasticsearch
 * Cloud and orchestration: AWS, including SageMaker, Redshift, and ECS, along with Airflow
 * Version control: GitLab
 * AI tools: Cursor, GitHub Copilot, and Claude Code
 * Observability: Datadog

## Description

SeatGeek is looking for a Machine Learning Engineer to help turn research and experimental models into reliable, production-ready machine learning systems. You will work closely with data scientists, product managers, and software engineers to build ML infrastructure and services that support millions of fans.

Your work will contribute to key areas of the business, including ticket discovery, personalized recommendations, pricing and inventory optimization, demand forecasting, and fraud prevention. The role combines software engineering, machine learning, and product development, with an emphasis on building scalable, maintainable systems that deliver measurable business value., * 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.
 * Collaborate with data scientists, product managers, and software engineers to move research and experimental models into production-ready systems.
 * Address technical challenges in the ticketing industry, including real-time pricing optimization, demand forecasting, and fraud detection.
 * Develop automated machine learning pipelines for training, validation, deployment, and monitoring using MLOps best practices.
 * Work across teams and disciplines to promote ML capabilities and integrate them into SeatGeek's core products.