Staff Machine Learning Engineer – Technical Lead
Company | Zoom |
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Location | Seattle, WA, USA, San Jose, CA, USA, Remote in USA |
Salary | $143000 – $312800 |
Type | Full-Time |
Degrees | Bachelor’s, Master’s |
Experience Level | Senior |
Requirements
- Bachelor’s or higher in Computer Science, Engineering, Mathematics, Statistics, or a related technical field, or equivalent practical experience.
- 4+ years of hands-on experience in machine learning, particularly within search, ranking, information retrieval, or natural language processing (NLP).
- Track record in building and deploying machine learning models in production, with experience in RAG (Retrieval-Augmented Generation) models or similar hybrid systems combining retrieval with generative models.
- Core stack: Python, Java, C++, or other programming languages for ML development.
- Understanding of search algorithms, ranking mechanisms, and information retrieval, specifically in context-driven search systems.
- Experience with ML frameworks like TensorFlow, PyTorch, Scikit-learn, or similar.
- Experience working on large-scale search or recommendation systems for consumer-facing applications (e.g., messaging platforms, video conferencing, or cloud-based productivity tools).
Responsibilities
- Develop and implement advanced machine learning techniques, including Retrieval-Augmented Generation (RAG), to enhance search systems.
- Build AI-driven search solutions that improve information retrieval and enable Zoom AI Companion to generate personalized, context-aware responses.
- Improve AI capabilities to interpret, prioritize, and act on retrieved data, delivering clear and actionable insights to users.
- Enhance Zoom AI Companion’s ability to provide intelligent summaries, action items, and insights from meetings, chats, files, and shared content.
- Collaborate with product managers, engineers, and research scientists to create powerful, context-driven search solutions.
- Strengthen the search foundation of Zoom’s AI Companion to deliver advanced meeting insights, actionable recommendations, and support decision-making.
Preferred Qualifications
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No preferred qualifications provided.