This role pays less than
68%
of similar roles. Most pay
$196,312–$254,750
— the shaded band above.
At the midpoint, this role pays about
$197k
versus about
$226k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
896 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
As a Senior Deep Learning Compiler Engineer - XLA on the XLA team, you will develop compiler optimization algorithms for deep learning workloads to improve inference and training performance for the JAX framework and OpenXLA compiler on NVIDIA GPUs at scale. Your daily responsibilities include crafting optimization techniques for network graphs, designing graph partitioning and tensor sharding for distributed systems, performing performance tuning, and generating code for GPU backends. You will utilize technologies including C/C++, MLIR, LLVM, OpenAI Triton, XLA, TVM, CUDA, and OpenCL. The role focuses on the technical challenge of accelerating next-generation deep learning software by collaborating with hardware architecture teams to design compiler features. You will solve complex problems related to high-performance computing and distributed programming while implementing user-facing features in JAX and associated libraries for large-scale AI systems.