R

Roku

Streaming hardware and ad-supported content

Staff Software Engineer - Demand Bidder, Ad Serving Platform

Backend EngineeringConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USA

About the Job

Requirements

  • At least 10 years of experience designing, building, and operating large-scale, low-latency distributed systems, ideally including a system built substantially from the ground up.
  • A demonstrated track record of owning complex systems end-to-end, including design, build, operations, on-call, and iteration based on production feedback.
  • Ability to ramp quickly on unfamiliar, complex, large codebases and become productive.
  • Experience evolving and refactoring live, business-critical systems without compromising uptime or correctness.
  • Strong command of Java and a solid foundation in algorithms, data structures, concurrency and multithreading, and performance optimization.
  • Practical experience with distributed caching, high-throughput messaging and streaming systems, and SQL and NoSQL datastores.
  • Comfort operating cloud infrastructure at scale, using GCP or AWS.
  • A B.S. or M.S. in Computer Science, Engineering, or equivalent practical experience.
  • Experience using AI coding assistants such as Claude Code or Cursor in real production work to accelerate design, implementation, debugging, and understanding unfamiliar codebases.
  • Informed opinions on how best to leverage AI coding assistants.
  • Curiosity about applying AI to monitor system health, triage issues, or develop agentic workflows.
  • A high bar for correctness and understanding of shipped work when using AI tools.

Responsibilities

  • Design, build, and operate core components of a large-scale, real-time distributed decisioning system with strict latency requirements.
  • Take end-to-end ownership of specific subsystems, including architecture, implementation, testing, deployment, on-call, and long-term evolution.
  • Build a working mental model of a highly distributed, complex production system and make high-leverage contributions.
  • Identify opportunities to continuously evolve the system and tooling.
  • Partner with engineers and applied scientists working at the intersection of distributed systems and statistical or machine-learning-driven decision-making.
  • Diagnose and resolve subtle issues, often related to timing or statistics, in a highly concurrent, multi-region distributed system.
  • Mentor other engineers and raise the bar on engineering rigor, testing discipline, and operational excellence across the team.
  • Communicate with technical and non-technical stakeholders and drive alignment across engineering, product, and business partners.

Desired Qualifications

  • Exposure to applying statistical, control-theory, or machine-learning-driven techniques within production decision-making systems.
  • Real-time bidding or ad-tech domain experience, or deep experience in adjacent high-stakes, low-latency domains such as trading systems, large-scale ranking or recommendation, matchmaking, or risk and fraud systems.
  • Genuine curiosity and willingness to help shape how the team uses AI responsibly.

About the Company

Roku

Streaming hardware and ad-supported content

Roku provides a streaming entertainment ecosystem built around hardware devices (Roku TVs, streaming players, smart home gear, and audio gear) and a purpose-built operating system. Its devices run the Roku OS to deliver apps and streaming content to televisions. The Roku Channel offers free, ad-supported content and Roku Originals are exclusive programs produced in-house, bundled with advertising revenue and content distribution. The business model blends hardware sales, advertising, and distribution of content through its platform. Roku differentiates itself by offering a wide range of affordable devices, a centralized ad-supported free channel, and in-house originals, creating an integrated yet open platform for apps and content. The company’s goal is to grow a large, easy-to-use streaming ecosystem that combines hardware, software, and content to reach many households and monetize through device sales, ads, and distribution deals.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Jose, CA
Founded
2002

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