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Machine Learning Engineer III - FES

1 hour, 18 minutes ago
United States
Full-time
Mid Level
Machine Learning Engineer
Data Science and Analytics
Apache Spark Databricks Kafka Python SageMaker SQL
Apply Now
Fanatics

Fanatics

Fanatics Inc is the top destination for officially licensed sports merchandise, offering a vast collection of fan gear from all your favorite teams and players. As a market leader in the sports industry, Fanatics is evolving into a global digital sport...

Retailing
5K-10K
Founded 2011
$4900M raised
View All Jobs 5

Description

  • Own the end-to-end machine learning infrastructure for recommendation, personalization, and LTV scoring systems from feature engineering through deployment and monitoring.
  • Build and maintain real-time and batch feature pipelines that support low-latency predictions across the FanApp recommendation experience and other personalization use cases.
  • Develop and scale model serving infrastructure for high-throughput, high-availability predictions across Fanatics' multi-product ecosystem.
  • Partner with Data Scientists to productionize LTV, churn, propensity, and ranking models and bridge experimentation into reliable production systems.
  • Build and maintain embedding pipelines that generate and refresh user and item representations for personalization and affinity modeling.
  • Implement and maintain A/B testing and experimentation infrastructure to measure model and feature impact in production.
  • Collaborate with Data Engineers, Analytics Engineers, and Product teams to identify data sources, enforce data quality standards, and ensure timely model inputs.
  • Drive improvements in model accuracy, latency, and throughput through iterative optimization and monitoring frameworks.

Requirements

  • 3–5+ years of experience in a machine learning engineering or data engineering role.
  • Degree in a quantitative field such as Computer Science, Mathematics, Statistics, Engineering, or equivalent.
  • Strong Python proficiency and deep familiarity with production ML workflows, including packaging, versioning, deployment, and monitoring.
  • Hands-on experience with end-to-end ML platforms such as Databricks, AWS SageMaker, or equivalent, including model registry and serving components.
  • Proven experience building real-time feature pipelines and model serving systems at scale with strict latency and uptime requirements.
  • Experience building or scaling recommendation or ranking systems in production, including embedding pipelines and low-latency inference infrastructure.
  • Solid understanding of distributed systems and large-scale data processing tools such as Spark, Kafka, or equivalent.
  • Strong SQL proficiency and experience with relational and dimensional data models.
  • Practical understanding of the mathematics underlying modern ML, including linear algebra, probability, and optimization.
  • Familiarity with experimentation infrastructure and A/B testing frameworks, including exposure bias handling and metric integrity in production environments.
  • Preferred: experience with feature stores such as Feast or Tecton.
  • Preferred: experience with ML observability tooling, including drift detection, prediction monitoring, and feature freshness alerting.

Benefits

  • Salary range of $117,000–$167,000 USD.
  • Base pay plus bonus eligibility.
  • Full-time employment with additional compensation and benefits.
  • Access to Fanatics benefits information through the company benefits portal.
  • Potential in-person interview or onboarding components, including onsite interviews or Launching into Better: LIVE in New York City for eligible hires.

Interested in this position?

Apply directly on the company website

Apply Now

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