AI Engineer

Zoom•San Jose, CA

11d•Hybrid

About The Position

Join Zoom AI Vertical team, start from the Zoom enterprise-level products; and drive innovation, development in AI-integrated projects. You will collaborate closely with teams from GenAI, Meeting, Phone, Big data, and Cloud to build business features for Zoom products. The ideal candidate will majorly focus on AI product feature innovation/creation, AI capability improvement, agentic pipeline, applications, data process/analysis, and full cycle software development. You will play the critical role in shaping the future of Zoom AI products. About the Team We are the AI/ML application engineering team dedicated to building cutting-edge products and providing business platforms and tools for enterprise customers. We are seeking an experienced candidate for AI feature development, model/pipeline optimization, and maintenance of end-to-end systems that power AI-driven. Our products have extensive developments based on the integrations with LLM, agent, ASR, and image processing, etc. These products are highly user-facing, friendly and robust applications.

Requirements

6+ years (or equivalent experience) of hands-on skills in AI/ML and software engineering.
Advance degree in Computer Science or related fields.
Have background on AI product architecture/system design and implementation/integration.
Demonstrate working knowledge of software development principles, design patterns, and scalable systems.
Have solid experience with one or more of the following: AI agent, RAG, NLP, recommendation, cloud platform, data retrieve/analysis, DB/SQL, A/B test.
Possess coding skills in Python, Java, or C/C++, etc.
Solid experience with LLM tuning, prompt engineering.
Have comprehension of machine learning theories, algorithms, and frameworks.
Possess familiarity with AI tools for daily development work.

Responsibilities

Collaborating with cross-functional teams to define, design, implement and release new AI features and innovative applications.
Demonstrating a high level AI product feature and architecture design.
Breakdown the pipeline into engineering subtasks and implementation details.
E2E development.
AI capability evaluation.
Prompt engineering.
Agentic AI creation.
Model tuning.
Ensuring reliability and high quality by participating in code reviews, testing, and debugging.
Building metrics, dashboards to measure the service performance and quality
Documenting test report, code, algorithms, and technical processes for internal and external references.
Driving task progress.