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Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at…
Staff-level ML engineer on YouTube's recommendation systems team: leads the design and implementation of retrieval/ranking recommendation models, optimizes ML infrastructure and model architecture, and provides technical leadership across teams. Requires deep ML expertise at large scale.
Software Engineer III on YouTube's Trust & Safety team in Zurich, building video content-understanding systems: ML classifiers across video, image, audio, transcript and metadata modalities, plus infrastructure that automates enforcement actions and routes content for review by humans or LLMs (Gemini). Core stack: C++, Python, SQL, and end-to-end machine learning.
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major…
Staff engineer on YouTube/Google Ads' video creatives team in Warsaw, building advertiser-facing video creation and enhancement tools in the Ads buyside frontend. Day to day: technical leadership and architecture, coaching a distributed team, and full-stack web work (TypeScript/React/Angular) integrating AI/LLM workflows like Gemini at massive scale.
Senior Software Engineer on YouTube's infrastructure team at Google, designing, building, and maintaining large-scale distributed systems that support YouTube at massive scale. Day-to-day work involves writing and testing system code in C++, leading design reviews, reviewing others' code, and triaging and debugging infrastructure issues.
Lead the YouTube Ads ML team at Google, managing engineers and setting technical roadmaps while building large-scale machine learning systems for ad recommendations. The role blends people management with hands-on deep learning work, applying GenAI models like Gemini at massive scale.
Software Engineer III on YouTube's Shopping Creator team in Zürich, designing and building AI/ML-driven models and LLM-integrated systems that help creators activate and scale shopping content, such as matching creators with merchants, offers, and products. Core stack includes C++, Python, and ML infrastructure.
Software Engineer III focused on optimizing YouTube's recommendation models for TPU efficiency. The role involves implementing quantization, knowledge distillation, and hardware-friendly architectures using C++, Python, and frameworks like TensorFlow or JAX to reduce costs and maximize performance.
Manage the backend infrastructure team powering YouTube Shorts creation and Remix features (AI and non-AI), including media generation infrastructure serving Shorts Creation, Effects, Posts, and YouTube Studio. Day to day: technical leadership, mentoring engineers, and driving cross-team alignment on large-scale backend systems.
Senior Software Engineer on YouTube's AI/ML team at Google, writing and testing production code, designing ML solutions, and leveraging ML infrastructure to debug and resolve issues at massive scale. Core technologies are Python, C++, and machine learning infrastructure (deployment, evaluation, optimization, data processing).
Software engineer on YouTube's Ads ML Infrastructure team, building the systems that train and serve ad-ranking models, improving fleet resource efficiency, and automating developer workflows. Core work involves large-scale C++ systems, ML infrastructure (deployment, optimization, data processing), and technologies like TensorFlow and LLMs.
Staff-level engineer on Google's YouTube Ads Creative Optimization (YACO) team, architecting and scaling the AI/ML infrastructure behind ad creative generation — distributed systems, creative data engines, rendering pipelines, and agentic frameworks for GenAI and heavy media workloads — while mentoring engineers and setting the technical roadmap.
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