Staff AI Engineer

Zoom • Seattle, WA

1d • $206,600 - $451,800 • Hybrid

About The Position

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.

Requirements

• A Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience
• 5+ years of software engineering experience, with significant time spent on inference systems or ML infrastructure at production depth
• Hands-on experience with at least one major inference framework: vLLM, TensorRT-LLM, SGLang, or ONNX Runtime (serving, not just export)
• GPU programming experience: CUDA kernel development, memory optimisation, and profiling with Nsight or equivalent tools
• Production experience serving LLMs or large vision models -- you've owned latency SLOs, debugged throughput regressions, and shipped optimisations that moved the needle
• Depth in at least two of: speculative decoding, continuous batching, KV cache design, quantisation pipelines, prefill/decode disaggregation
• Strong systems instincts in Python and C++; ability to read and modify framework internals

Nice To Haves

• Advanced degree (Master's or PhD) in a relevant technical field
• Experience with MoE models or 100B+ parameter deployments
• Familiarity with disaggregated serving architectures or multi-node inference
• Background in compiler-level optimisation (XLA, Triton, or similar)

Responsibilities

• 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

Benefits

• Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.
• Location based compensation structure
• Award-winning workplace culture
• Commitment to delivering happiness
• Benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways.
• Opportunities to stretch your skills and advance your career in a collaborative, growth-focused environment.
• Fair hiring practices that ensure every candidate is evaluated based on skills, experience, and potential.
• Accommodation during the hiring process

What This Job Offers

• Job Type: Full-time
• Career Level: Senior