軟體工程師:53,003 個職缺
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Senior Software Engineer
Senior engineer on the Pear Deck Learning team (K-12 EdTech) building full-stack features across Node.js/Express and Go gRPC backends and a React 18/TypeScript frontend, with real-time infrastructure, polyglot data, AWS/GCP ops, and LLM integrations serving hundreds of thousands of teachers and students in real time.
Senior Software Engineer, Backend & Data Platform
Senior backend engineer on Roku's Content Platform team in Bengaluru, designing and optimizing distributed data pipelines and real-time processing systems using Java, Spring Boot, Spark, Kafka, and Flink at large scale.
Senior Software Engineer, Backend
Senior backend engineer on Roku's Content Management System team, designing and building scalable microservices, data pipelines, and APIs that power content ingestion, metadata, and curation for the Roku Channel streaming platform, using Java/Scala/Python on AWS/GCP with NoSQL and RDBMS stores.
Software Engineer, Agentic AI
Design, build, and deploy AI agents and copilots for Roku TV, owning end-to-end agentic systems from prototyping through production. Work hands-on with LLMs, RAG pipelines, multi-agent orchestration, MCP/tool integrations, and evaluation/observability frameworks using Python, C/C++, and cloud-native deployments.
Senior Software Engineer - Ads Analytics
Senior Software Engineer on Roku's Data Insights team designing and building scalable APIs, backend services, and big-data pipelines that power ad measurement and analytics. Works with Spring Boot, Apache Spark, Airflow, Druid, Trino, and StarRocks in a hybrid San Jose role.
Senior Software Engineer, Machine Learning
Senior ML engineer on Roku's Recommendation team in Bengaluru, building and productionizing recommendation, ranking, and optimization systems for advertising and media planning on the Roku TV streaming platform using Python, Java, Spark, and large-scale distributed ML infrastructure.
Software Engineer, Embedded Agentic AI
Designs and ships production AI agents and copilots for Roku TV, owning the full lifecycle from prompt/context design and orchestration through RAG pipelines, MCP and tool integrations, evaluation, and observability — embedded in resource-constrained TV environments.