PrizePicks is the fastest-growing sports company in North America according to the 2023 Inc. 5000 rankings, two years running, and the largest independent skill-based fantasy sports operator in the country.

Staff Machine Learning Engineer – Personalization

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteTeam 201-500H1B No SponsorCompany Site LinkedIn

Location

United States

Posted

37 days ago

Salary

$220K - $280K / year

7 yrs expEnglishAWSBig QueryCloudDynamo DBGoogle Cloud PlatformKafkaPythonRedisRustSQLGo

Job Description

• Architect the Hybrid Engine: Design and build the "Project Bridge" architecture, transitioning the platform from heuristic-based logic (Cohort/Geo-based) to fully real-time ML personalization (Vector Search/Neural Networks). • Real-Time Inference at Scale: Steer the design and deployment of low-latency services (Segment Service & User Profile Service) using Redis/DynamoDB to serve personalized board orderings, deposit defaults, and "For You" feeds in milliseconds. • Feature Engineering & Data Strategy: Partner with Data Science to build the logging pipelines that tag why a user saw an item (data labeling). You will create the feature store required to train future neural networks for individual-level personalization. • Solve the "Cold Start" Problem: Implement logic for dynamic league ordering and deposit smart-defaults based on geospatial data and initial user cohorts, ensuring immediate relevance for new users.

Job Requirements

7+ years of experience in Backend/ML Engineering with a specific focus on Recommendation Systems (RecSys) or Personalization engines in production.
3+ years of technical leadership, acting as a lead and driving architecture decisions for high-traffic consumer applications.
Experience with Real-Time Data: Proficient in streaming architectures (Kafka/PubSub) and low-latency lookups (Redis, DynamoDB) to serve model inference in <200ms.
MLOps Experience: Experience with the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, or Databricks.
Strong Coding Skills: Expert in Python and SQL; proficiency in Go or Rust is a strong plus for high-performance inference layers.
Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE) or AWS equivalents.

Benefits

Company-subsidized medical, dental, & vision plans
401(k) plan with company match
Annual bonus
Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
Generous paid leave programs, including 16-week paid parental leave and disability benefits
Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
Company-wide in-person events and team outings
Lifestyle enhancement program
Company equipment provided (Windows & Mac options)
Annual performance reviews with opportunities for growth and career development