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.
Roku is the leading TV streaming platform in the US, with a mission to connect the entire TV ecosystem by helping consumers discover content, enabling publishers to grow audiences, and giving advertisers powerful ways to engage viewers.
About the TeamThe Ad Engineering team builds the platform behind Roku's advertising business. Within Ad Engineering, the Business Applications team owns the systems and tooling that power the advertising revenue lifecycle. The platform internal teams and advertisers rely on to plan, price, book, and grow campaigns at scale.
About the RoleWe are hiring a Senior Engineer to lead the architecture and implementation of a next-generation, agent-native, AI-powered business applications platform. This is a high-impact role focused on building intelligent, recommendation-driven experiences that make day-to-day revenue decisions with pricing, booking, upsells, retention, and media planning faster, smarter, and more accessible to the teams that run Roku's advertising business.
You will architect and build the end-to-end system for AI-driven recommendations and decisioning, from business and customer signals through to actionable, validated outputs. You will work closely with ML, backend, frontend, data, and business stakeholders to deliver a production-ready platform that improves speed, accuracy, and scalability across the advertising revenue workflow.
What You'll Do- Define the technical architecture and overall stack for an agent-native business applications platform spanning pricing guidance, booking and order intelligence, upsell recommendations, churn and retention prediction, media planning, deal scoring, revenue forecasting, and more.
- Evaluate LLMs, multimodal systems, multi-agent orchestration frameworks, and recommendation, ranking, and forecasting models for product use.
- Design and build the pipeline from business and customer signals to model inference, recommendation generation, output validation, and integration with internal revenue systems and APIs.
- Build production-grade systems with strong error handling, output validation, explainability, auditability, and human-in-the-loop guardrails for high-stakes pricing and financial decisions.
- Partner cross-functionally with ML, backend, frontend, data, and business teams to iterate quickly based on feedback and business needs.
- Drive technical decisions that directly influence revenue impact, product quality, scalability, and time-to-market.
- Bachelor's degree in Computer Science or a related field.
- Experience building recommendation or decisioning systems, ideally in advertising, media, or revenue-platform environments.
- Strong understanding of modern LLMs and agentic systems, and the ability to evaluate latency, cost, and quality tradeoffs.
- Solid experience with LLM and multi-agent pipelines, including prompting, tool use, orchestration, tradeoff analysis, and error handling.
- Experience deploying ML systems in production, including model serving, containerization, CI/CD, and monitoring.
- Hands-on experience with modern ML frameworks and tooling such as PyTorch, Hugging Face Transformers, agent orchestration frameworks (e.g., LangGraph or similar), feature stores, and vector databases for RAG workflows.
- Experience designing evaluation approaches for recommendation and generative systems using human review, automated and offline metrics, and online A/B testing.
- Strong software engineering fundamentals and solid production experience in Java or Python.
- Ability to translate ambiguous business requirements into practical technical solutions and communicate tradeoffs clearly to cross-functional partners.
- Startup or founding-engineer experience, or experience leading fast-moving Gen AI or agentic product initiatives.
- Experience owning a business-facing or self-serve product from architecture through production deployment and operational support.
- Deeper background in recommendation systems, pricing optimization, demand forecasting, uplift and churn modelling, or quoting and optimization.
- Experience improving inference cost and latency, and building responsible AI guardrails such as safety, compliance, auditability, and human review mechanisms.
- Open-source contributions or publications in ML, recommender systems, or applied AI for revenue and decisioning.
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). 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 [email protected].
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.
To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.
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 [email protected].
Skills Required
- Bachelor's degree in Computer Science or a related field.
- Experience building recommendation or decisioning systems, ideally in advertising, media, or revenue-platform environments.
- Strong understanding of modern LLMs and agentic systems, and ability to evaluate latency, cost, and quality tradeoffs.
- Solid experience with LLM and multi-agent pipelines, including prompting, tool use, orchestration, tradeoff analysis, and error handling.
- Experience deploying ML systems in production, including model serving, containerization, CI/CD, and monitoring.
- Hands-on experience with ML frameworks and tooling such as PyTorch, Hugging Face Transformers, agent orchestration frameworks (e.g., LangGraph), feature stores, and vector databases for RAG workflows.
- Experience designing evaluation approaches for recommendation and generative systems using human review, automated/offline metrics, and online A/B testing.
- Strong software engineering fundamentals and production experience in Java or Python.
- Ability to translate ambiguous business requirements into practical technical solutions and communicate tradeoffs to cross-functional partners.
- Startup or founding-engineer experience or leading fast-moving Gen AI/agentic product initiatives.
- Experience owning a business-facing or self-serve product from architecture through production deployment and operational support.
- Deeper background in recommendation systems, pricing optimization, demand forecasting, uplift/churn modelling, or quoting and optimization.
- Experience improving inference cost/latency and building responsible AI guardrails (safety, compliance, auditability, human review).
- Open-source contributions or publications in ML, recommender systems, or applied AI for revenue and decisioning.
Roku Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Roku and has not been reviewed or approved by Roku.
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Fair & Transparent Compensation — Pay is positioned as competitive across many roles, with frequent emphasis on strong base and total compensation relative to market expectations. Fair-pay perception appears comparatively stronger than overall satisfaction with the broader rewards package.
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Healthcare Strength — Healthcare coverage is framed as a standout, with sizable employer premium contributions that can reduce employee premiums significantly depending on plan choice. Preventive care and mental-health support are also described as part of the core offering.
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Leave & Time Off Breadth — Time-off offerings are presented as broad, including paid holidays, PTO, and multiple leave categories such as bereavement and family-related leave. Self-managed or “unlimited” PTO is also described for many salaried roles, supporting flexibility in taking time off.
Roku Insights
What We Do
Roku pioneered streaming to the TV. We connect users to the streaming content they love, enable content publishers to build and monetize large audiences, and provide advertisers with unique capabilities to engage consumers. Roku streaming players and Roku TV™ models are available around the world through direct retail sales and licensing arrangements with TV OEMs and service operators.
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