Senior AI/ML Software Engineer, YouTube Knowledge
GoogleJobsCloseBy Editorial Insights
Google seeks a Senior AI/ML Software Engineer for YouTube Knowledge in Paris, a full-time onsite role focused on ML infrastructure, model deployment, and GenAI initiatives at YouTube scale. You will design, test, deploy, and improve software across ML domains while collaborating across teams on high impact projects. Minimum qualifications: 5+ years of software development, 3+ years testing or launching software, 1 year in design or architecture, and 3 years in ML areas such as speech, reinforcement learning, or ML infrastructure. Preferred: Master or PhD, 5 years in data structures and algorithms, leadership, and accessibility work. France salary €104k-€106k plus 15% bonus, equity, and benefits. Apply with a results driven resume showing end-to-end ownership, scalable pipelines, measurable impact, and collaboration; highlight GenAI, NLP or speech projects and readiness to discuss design trade-offs and scale.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 5 years of experience with data structures and algorithms.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
About the job
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 massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
We are working on a variety of issues including infrastructure, complex algorithms, data mining, and machine learning including Large Language Models (LLMs) and GenAI. We process data sets at YouTube scale (billions of users, videos and watch time hours). We apply those techniques to improve impactful products from YouTube including Home, Search, Recommendations and vertical experiences (Music, Youth, Gaming, Living Room, etc.) We cover both infrastructure and data quality in all our projects, and do a fair number of exploration projects.
Most of our work is directly impacting YouTube's top priorities including responsibility, and families Initiatives.
France: €104000 - €106000 (EUR) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write and test product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.