Job description

Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. About the team The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers, and Roku. The systems and solutions span multiple disciplines and technologies to perform real-time multi-objective optimization across distributed systems at large scale and with low latency. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation, and Inference Platform, which powers the entire landscape, and we continuously evolve. About the role We are seeking a talented and experienced Senior Software Engineer, MLOps/DevOps, to join the Advertising Performance team and play a critical role in supporting and scaling our Machine Learning infrastructure. The ideal candidate has a strong background in DevOps/SRE practices, cloud infrastructure management, and MLOps tooling — with a passion for building platforms that accelerate ML experimentation and deployment at internet scale. You will partner closely with ML Scientists and Engineers to streamline the end-to-end ML lifecycle across training, evaluation, deployment, and monitoring — on top of a modern, cloud-native stack running on GCP and AWS using Kubernetes, Apache Airflow, Spark, Ray, MLflow, Chronon, etc. What you’ll be doing Lead the design and operation of scalable, production-grade cloud infrastructure for ML workloads across AWS and GCP, including GPU/TPU-based training and inference environments Architect and improve CI/CD systems for ML models and platform services to enable fast, reliable, and safe production releases Own and evolve low-latency infrastructure for real-time model inference, including KV store and vector databases Define and enforce observability standards for ML systems, including model performance monitoring, drift detection, capacity planning, and pipeline health metrics Participate in on-call rotation, leading incident response and root-cause analysis for critical ML training and serving infrastructure Partner with data scientists and ML engineers to improve platform usability, accelerate model iteration, and implement strong MLOps and SRE best practices Champion operational excellence across ML infrastructure through automation, resilience engineering, disaster recovery planning, and continuous improvement We’re excited if you have BS or MS in Computer Science, Engineering, or a related quantitative field Ability to demonstrate AI tool (Claude, Cursor, ChatGPT etc.) coding efficiency at an advanced skill level 8+ years of experience in DevOps, SRE, or ML infrastructure, including 4+ years supporting large-scale ML or AI systems Strong programming skills in Python and/or Scala or Java for platform automation and tooling Deep experience with Kubernetes and container orchestration on GCP (GKE) and/or AWS (EKS) Expertise with NoSQL or low-latency data stores such as Aerospike or similar technologies Hands-on experience with data and orchestration technologies such as Apache Spark, Apache Flink, Apache Airflow, and Kafka Experience building and maintaining CI/CD systems using tools such as Jenkins or GitLab Runner Familiarity with feature engineering platforms such as Chronon and model lifecycle tools such as MLflow Strong infrastructure-as-code experience with Terraform or similar tooling Experience with observability platforms such as Prometheus, Grafana, and Datadog Excellent communication and cross-functional collaboration skills Experience in the Advertising domain is a plus #LI-DH2 What's Roku's approach to hybrid working? 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. What are some of the benefits? Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include 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. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter. Accommodations 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 . What should I know about Roku's culture? Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.  We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.  To learn more about Roku, our global footprint, and how we've grown, visit weareroku.com . By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice , and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com .

Requirements

Must-haves

Teamwork makes the stream work.
Roku is changing how the world watches TV
About the team
What you’ll be doing
Lead the design and operation of scalable, production-grade cloud infrastructure for ML workloads across AWS and GCP, including GPU/TPU-based training and inference environments
Architect and improve CI/CD systems for ML models and platform services to enable fast, reliable, and safe production releases
Own and evolve low-latency infrastructure for real-time model inference, including KV store and vector databases
Define and enforce observability standards for ML systems, including model performance monitoring, drift detection, capacity planning, and pipeline health metrics
Participate in on-call rotation, leading incident response and root-cause analysis for critical ML training and serving infrastructure
Partner with data scientists and ML engineers to improve platform usability, accelerate model iteration, and implement strong MLOps and SRE best practices
Champion operational excellence across ML infrastructure through automation, resilience engineering, disaster recovery planning, and continuous improvement
We’re excited if you have
BS or MS in Computer Science, Engineering, or a related quantitative field
Ability to demonstrate AI tool (Claude, Cursor, ChatGPT etc.) coding efficiency at an advanced skill level
8+ years of experience in DevOps, SRE, or ML infrastructure, including 4+ years supporting large-scale ML or AI systems
Strong programming skills in Python and/or Scala or Java for platform automation and tooling
Deep experience with Kubernetes and container orchestration on GCP (GKE) and/or AWS (EKS)
Expertise with NoSQL or low-latency data stores such as Aerospike or similar technologies
Hands-on experience with data and orchestration technologies such as Apache Spark, Apache Flink, Apache Airflow, and Kafka
Experience building and maintaining CI/CD systems using tools such as Jenkins or GitLab Runner
Familiarity with feature engineering platforms such as Chronon and model lifecycle tools such as MLflow
Strong infrastructure-as-code experience with Terraform or similar tooling
Experience with observability platforms such as Prometheus, Grafana, and Datadog

Nice-to-haves

Experience in the Advertising domain is a plus

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaimlgcpawskubernetesci/cdpythonjava

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Wellness