Senior ML Engineer, Real-Time Ad Tech Platform

Roku, Inc.; Austin (TX); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Mental health resources

Financial wellness resources

Healthcare (medical, dental, vision)

Life insurance

Disability insurance

Commuter benefits

Retirement plan (401(k) / pension)

Job summary

Roku, Inc. is hiring a senior ML engineer to help build and operate a comprehensive ML platform that manages the full model lifecycle from feature engineering to deployment.

You will work on data analysis, feature engineering, and model training for real-time and batch prediction scenarios, collaborating with product, data science, and software teams to drive impactful ad performance improvements.

Qualifications

• Bachelor's/Master's/PhD in Computer Science, Statistics, or related field.
• 5+ years of applied ML experience on real use cases.
• Proficient coding in Spark, Python, or Java.
• Familiarity with real-time evaluation of models with low latency.
• Experience with distributed ML frameworks (Spark-MLlib, TensorFlow).

Responsibilities

• Build a first-class ML platform covering feature engineering, training, versioning, deployment, and monitoring.
• Perform data analysis and feature engineering for multiple models.
• Develop models with batch and real-time prediction scenarios.
• Maintain and optimize production ML pipelines and systems.
• Collaborate with product managers, data scientists, and engineers to deliver impactful solutions.
• Keep up with emerging ML technologies and industry trends.

Skills

Machine Learning

Spark

Python

Java

Real-time evaluation

Distributed ML

Spark-MLlib

TensorFlow

Spark/Hive/NoSQL

AI tools

Education

Bachelor's degree

Master's degree

PhD

Tools

Hive

Aerospike

ScyllaDB

Job description

Roku, Inc. is hiring a senior ML engineer to help build and operate a comprehensive ML platform that manages the full model lifecycle from feature engineering to deployment.

You will work on data analysis, feature engineering, and model training for real-time and batch prediction scenarios, collaborating with product, data science, and software teams to drive impactful ad performance improvements.