Das ist der Job
Conduct and publish original research that pushes the pareto frontier for the field of ML Systems
Darum lohnt es sich
You’ll collaborate across inference, compiler, scheduling, and performance teams to push the frontier of accelerated computing for AI. We are seeking highly skilled and motivated software engineers to join us and build AI inference systems that serve large-scale models with extreme efficiency.
You’ll architect and implement high-performance inference stacks, optimize GPU kernels and compilers, drive industry benchmarks, and scale workloads across multi‑GPU, multi‑node, and multi‑cloud environments.
What You’ll Be Doing Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding, data/tensor/expert/pipeline‑parallelism, prefill‑decode disaggregation.
Develop, optimize, and benchmark GPU kernels (hand‑tuned and compiler‑generated) using techniques such as fusion, autotuning, and memory/layout optimization; build and extend high‑level DSLs and compiler infrastructure to boost kernel developer productivity while approaching peak hardware utilization.
Define and build inference benchmarking methodologies and tools; contribute both new benchmark and NVIDIA’s submissions to the industry‑leading MLPerf Inference benchmarking suite. Architect the scheduling and orchestration of containerized large‑scale inference deployments on GPU clusters across clouds.
