AI Engineer
Role details
Job location
Tech stack
Job description
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., * 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
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
Preferred
- 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)
Benefits & conditions
3.73.7 out of 5 stars 1116 NW 54th St, Seattle, WA 98107 Hybrid work $151,800 - $332,200 a year - Full-time, $151,800.00
Maximum: $332,200.00
In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.
Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience.
We also have a location based compensation structure; there may be a different range for candidates in this and other locations., As part of our award-winning workplace culture and commitment to delivering happiness, our 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.