ML infrastructure: Help build a first-class machine learning platform from the ground up which manages the entire model lifecycle - feature engineering, model training, versioning, deployment, online serving/evaluation, and monitoring prediction quality
Data analysis and feature engineering: Apply your expertise to identify and generate features that can be leveraged by multiple use cases and models
Model training with batch and real-time prediction scenarios: Use machine learning and statistical modeling techniques such as Decision Trees, Logistic Regression, Neural Networks, Bayesian Analysis and others to develop and evaluate algorithms for improving product/system performance, quality, and accuracy
Production operations: Low-level systems debugging, performance measurement, and optimization on large production clusters
Collaboration with cross-functional teams: Partner with product managers, data scientists, and other engineers to deliver impactful solutions
Staying ahead of the curve: Continuously learn and adapt to emerging technologies and industry trends

Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field
Demonstrated production experience in applied machine learning, with PhD-level research and implementation experience considered a strong accelerator
Great coding skills and strong software development experience (we use Spark, Python, Java)
Familiarity with real-time evaluation of models with low latency constraints
Familiarity with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc
Ability to work with large scale computing frameworks, data analysis systems, and modeling environments. Examples include Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB

Global access to mental health and financial wellness support and resources
Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension)
Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs

Hybrid

Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. Fridays are generally flexible for remote work, except for employees whose specific roles or assigned office location require five days' a week attendance.
Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.

Roku is hiring a Senior Machine Learning Engineer - AdTech