AI-Driven Backend Engineer (Remote/Hybrid)

Zoom; Seattle (WA); Hybrid; USD 184,030 - 275,400; Full time

Job summary

Zoom Communications, Inc. is seeking a Software Engineer focused on backend development and AI-embedded applications. You will design and implement web-based features and collaborate with AI, Meeting, Phone, Big Data, Data Engineering, and Cloud-Native teams.

The role emphasizes building scalable services, ML model deployment, testing, and documentation, with a structured hybrid work model and location-based compensation.

Qualifications

• Bachelor's degree in Computer Science, MIS, or related field or foreign degree equivalent.
• 3 years of experience deploying ML models into production, including evaluation and monitoring.
• 3 years building and operating scalable software/microservices exposing AI via APIs/SDKs.
• 3 years creating automated tests, CI/CD pipelines, and observability for AI/ML releases.
• 3 years designing data pipelines for model training and inference, with data validation and versioning.
• 3 years authoring technical docs for algorithms, system architecture, and runbooks.

Responsibilities

• Collaborate with product, research, and platform teams to clarify objectives and success metrics.
• Design, develop, and maintain AI/ML algorithms and production services (AI agents, CV, NLP, recommender).
• Implement end-to-end model lifecycle: data ingestion, feature engineering, training, evaluation, deployment, monitoring.
• Ensure quality by code reviews, automated tests, debugging, and addressing performance regressions.
• Document code, models, data pipelines, and runbooks for internal/external use.

Skills

ML models

Microservices

CI/CD pipelines

Data pipelines

Technical documentation

Education

Bachelor's degree in Computer Science, MIS or related field

Job description

Zoom Communications, Inc. is seeking a Software Engineer focused on backend development and AI-embedded applications. You will design and implement web-based features and collaborate with AI, Meeting, Phone, Big Data, Data Engineering, and Cloud-Native teams.

The role emphasizes building scalable services, ML model deployment, testing, and documentation, with a structured hybrid work model and location-based compensation.