Staff ML Engineer — Real-Time AI for DFS (Remote)

PrizePicks; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

PrizePicks, the fastest-growing sports company in North America, is hiring a Staff Machine Learning Engineer to scale and productionize core ML capabilities across DFS ecosystems. You will impact Time-to-Bet, Deposit Velocity, and Platform Integrity by deploying low-latency models.

You will architect scalable ML systems, enable real-time inference, lead feature store data strategy, and drive end-to-end MLOps practices to catch data drift and model degradation quickly.

Qualifications

• 7+ years of experience in ML engineering or backend engineering in production.
• 3+ years of technical leadership driving architecture decisions for consumer apps or scalable backends.
• Experience with real-time data streaming (Kafka/Flink/PubSub) and building low-latency services (<100ms).
• ML lifecycle management including training, deployment, monitoring using MLFlow, Kubeflow, Databricks or SageMaker.

Responsibilities

• Architect scalable ML systems and productionize models.
• Design low-latency real-time inference services across the platform.
• Lead data strategy and build a centralized feature store for training complex models.
• Own end-to-end MLOps: CI/CD, monitoring, retraining pipelines.

Skills

Machine Learning Engineering

Backend Engineering

Leadership

Real-Time Inference

Python

SQL

Go/C++/Rust

Cloud Native

Tools

MLFlow

Kubeflow

Databricks

SageMaker

Kafka/Flink

Job description

PrizePicks, the fastest-growing sports company in North America, is hiring a Staff Machine Learning Engineer to scale and productionize core ML capabilities across DFS ecosystems. You will impact Time-to-Bet, Deposit Velocity, and Platform Integrity by deploying low-latency models.

You will architect scalable ML systems, enable real-time inference, lead feature store data strategy, and drive end-to-end MLOps practices to catch data drift and model degradation quickly.