Machine Learning Platform Engineer (AI)

TL;DR

Machine Learning Platform Engineer (MLOps): Building and scaling a robust ML platform to productionize core machine learning capabilities with an accent on low-latency inference and high-availability infrastructure. Focus on designing end-to-end MLOps pipelines, developing a centralized feature store, and optimizing real-time model serving.

Location: Must be based in the U.S. (Atlanta, GA preferred)

Salary: $135,000 – $160,000

Company

The fastest-growing sports company in North America, providing a leading platform for Daily Fantasy Sports (DFS).

What you will do

• Design and build end-to-end ML infrastructure to transition experimental models into high-availability production services.
• Develop automation for low-latency real-time inference services (<100ms) to power decisions for risk analysis and oddsmaking.
• Lead the creation and optimization of a centralized feature store bridging batch historical data with real-time event streams.
• Implement MLOps best practices for CI/CD, model monitoring, and automated retraining pipelines to prevent data drift.
• Collaborate with the Infrastructure team to operate core ML components and improve the overall developer experience.

Requirements

• 3+ years of experience in Platform Engineering with a proven track record of deploying scalable ML platforms in high-traffic environments.
• 1+ years of experience owning ML systems end-to-end in production, including on-call and incident response.
• Proficiency in streaming architectures (Kafka, Flink, or PubSub) and building low-latency services.
• Deep experience with MLOps tools (SageMaker, VertexAI, Vector DBs) and scaling caches like Redis or Elasticsearch.
• Expertise in Python and containerization using Docker and Kubernetes.
• Must be authorized to work for any employer in the U.S. (No sponsorship available).

Nice to have

• Proficiency in Go, C++, or Rust for building high-performance inference layers.
• Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
• Experience enabling self-service capabilities for ML and Data Science teams.
• Experience integrating AI agents and AI coding tools into the development lifecycle.

Culture & Benefits

• Company-subsidized medical, dental, and vision plans.
• 401(k) plan with company match and annual performance bonus.
• Flexible PTO and generous paid leave programs, including 16-week paid parental leave.
• Workplace flexibility with modern schedules focused on deliverables rather than hours clocked.
• Company-provided equipment (Windows or Mac options) and regular career development reviews.