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
A highly scalable, highly available, real-time advertising platform is critical to support and grow Roku's rapidly expanding ad business. It is the mission of the Ad Engineering Team to build this platform. We are hiring a Senior Machine Learning Engineer, Advertising Platform, to be a vital part of this mission. If you bring extensive experience building complex systems using Machine Learning and Data Science, love great technology at scale, enjoy mentoring, jumping in, and figuring things out in any system, this role is for you!
The Ad Serving team is responsible for ensuring that ads on the Roku platform are relevant and of good quality, leading to better outcomes for advertisers and providing a great experience for our viewers. Dealing with millions of ad requests in a day, we need to have best in class ML driven systems to improve the way we serve ads in multiple countries and languages.
About the role
In this role, you will build and develop ML models to solve for content understanding aspects of Ads. These models rely on the visual, audio and textual content of ads, across multiple languages. This includes developing computer vision and machine learning models/methods such as deep learning models, generative AI solutions, large language models (LLMs) and vision language models (VLMs). You will work with software engineers and other ML engineers to identify, build, train and productionize these models to improve brand safety, increase revenue opportunities and help with moderation and generation of ad creatives in general
What you will be doing
Develop scalable and effective machine-learning models and optimization strategies to solve business problems related to Ads
Run regular A/B experiments, gather data, and perform statistical analysis
Work closely with software engineers and other ML engineers to deliver end-to-end solutions into production
Improve the scalability, efficiency and automation of ML driven ad serving systems, model training, deployment and serving
Partner with senior stakeholders to plan and drive the ML strategy for Ad Serving
We're excited if you have
Experience in a tech lead role delivering large cross-functional projects
Experience with SOTA technology/frameworks/Infra for Modeling
Worked at and contributed/led efforts at businesses where ML/Modeling is done at large scale/low latencies
Experience developing and implementing deep learning algorithms, particularly with respect to computer vision
Exceptional understanding of regression, classification, tree-based approach, neural networks, sequence-based, and NLP approaches like W2V or Bert
Experience brainstorming and identifying the right KPIs and objective functions.
Capacity to start off independently as the inaugural Ad Serving team hire in Cambridge
AI growth mindset
Publications at top-tier peer-reviewed conferences or journals (preferred)
Advertising or adjacent domain experience (preferred)
PhD in a relevant filed (preferred)
Our Hybrid Work Approach
Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy.
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). Our employees can take time off work for vacation and other personal reasons to balance 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 .
The Roku 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.
