AI Engineer

• Seattle, Washington, United States
• Full time

What You Can Expect

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You'll design, implement, and own the inference systems that serve Zoom's AI models at production scale - across real-time communication, vision, and language workloads. You'll be hands-on with kernel-level optimisation, inference framework internals, and production serving infrastructure, working closely with research and platform teams to push the boundary on latency, throughput, and cost.

About the Team

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You will join a dynamic AI Infrastructure team focused on enabling high-performance AI across Zoom's products and services. The team builds the core systems that support model training, deployment, and inference at scale, driving innovation in areas such as real-time communication, computer vision, and natural language understanding.

Responsibilities

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• Design and build high-performance inference serving systems for large-scale transformer and multimodal models (including 100B+ and MoE architectures)
• Implement and tune inference optimisations: speculative decoding, continuous batching, KV cache management, prefill/decode disaggregation, and quantisation (INT4/INT8/FP8)
• Contribute to and customise inference frameworks (vLLM, TensorRT-LLM, SGLang, or equivalent) for Zoom's production requirements
• Write and profile CUDA kernels and custom ops where framework-level optimisation is insufficient
• Own end-to-end deployment: from model packaging and serving API design to latency SLO monitoring and incident response
• Partner with research to translate model architecture changes into inference-efficient implementations
• Drive technical design and set the bar for inference engineering practices across the team

What We're Looking For

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* A Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical exp...