Senior ML Engineer — Knowledge Graph & AI Search Systems

Zoom; Seattle (WA); Hybrid; USD 157,440 - 236,200; Full time

Job summary

Zoom Communications, Inc. is seeking a Machine Learning Engineer to help design, implement, and optimize knowledge graph services and AI-powered search at scale.

You will deploy ML models in a microservice environment, collaborate with cross‑functional teams, and maintain documentation using Confluence, Zoom Docs, and LucidChart.

This role emphasizes robust data pipelines, security, and scalable architectures, with a hybrid/remote work approach across the U.S.

Qualifications

• Bachelor’s degree in CS or related field.
• 3+ years in document understanding pipelines.
• 3+ years deploying ML models in microservices with Docker/Kubernetes (AWS EKS).
• 3+ years evaluating external data for AI search/document understanding.
• 3+ years building metrics and monitoring for AI search pipelines.
• 3+ years data ingestion, preprocessing, transformation pipelines.
• 3+ years architecting ML workflows for knowledge graphs and search.
• 3+ years collaborating with cross‑functional teams.
• 3+ years optimizing knowledge graph algorithms.
• 3+ years researching ML/NLP/knowledge graphs.
• 3+ years developing AI‑driven search and ranking algorithms.
• 3+ years documenting AI search systems with Confluence/Zoom Docs/LucidChart.
• 3+ years routing requests to ML models and managing feature stores.
• 3+ years implementing auth and security (JWT, AWS KMS).
• Telecommuting allowed: may work anywhere in the U.S.

Responsibilities

• Architect and optimize large-scale ML workflows for knowledge graphs and search services.
• Deploy, monitor, and maintain ML models in a Docker/Kubernetes environment.
• Collaborate with engineers, PMs, and domain experts to define requirements.
• Maintain documentation for AI search systems using Confluence, Zoom Docs, and LucidChart.
• Develop business logic for routing requests to ML models and managing feature stores.
• Implement authentication and security for ML pipelines (JWT, KMS).
• Lead AI search pipelines design, including document understanding and retrieval.
• Develop performance metrics and monitoring for scalable, low-latency AI search.

Skills

Docker

Kubernetes

LLMs

Knowledge graphs

NLP

AI search

Cloud platforms

AsyncMQ

Python

Education

Bachelor's degree in CS or related field

Tools

Confluence

Zoom Docs

LucidChart

Docling

AWS EKS

ZCP

Job description

Zoom Communications, Inc. is seeking a Machine Learning Engineer to help design, implement, and optimize knowledge graph services and AI-powered search at scale.

You will deploy ML models in a microservice environment, collaborate with cross‑functional teams, and maintain documentation using Confluence, Zoom Docs, and LucidChart.

This role emphasizes robust data pipelines, security, and scalable architectures, with a hybrid/remote work approach across the U.S.