Senior Machine Learning Applications and Compiler Engineer, LPX

Nvidia

Actively hiring
Remote (Us, Ca, Santa Clara, US) Posted 70 days ago $152,000–$241,500 / year
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At a glance

AI generated

TL;DR

Join NVIDIA as a Senior Machine Learning Applications and Compiler Engineer to develop high-performance runtime and compiler components for our LPX inference stack. You will work on mapping neural network workloads onto future NVIDIA platforms, extending the software ecosystem with libraries and tooling for seamless model deployment across various platforms. Your responsibilities include benchmarking performance metrics, collaborating with hardware architects, and prototyping new compilation techniques such as graph transformations and memory optimizations tailored to spatial processors. Ideal candidates have a strong background in systems programming (C/C++, Rust), experience with LLVM/MLIR, familiarity with deep learning frameworks like TensorFlow and PyTorch, and contributions to open-source ML projects or research publications at top-tier venues.

Skills

C/C++ Rust LLVM MLIR TensorFlow PyTorch ONNX GPU Profiling tools Tracing tools Benchmarking tools CI/CD Parallel computing Heterogeneous computing Spatial architectures Dataflow architectures Large-scale AI systems

What you'll do

  • Develop high-performance runtime and compiler components for end-to-end inference optimization.
  • Define mappings of large-scale inference workloads onto NVIDIA’s systems.
  • Extend NVIDIA’s software ecosystem by contributing to libraries and tooling for model deployment.
  • Benchmark performance metrics to ensure efficient neural network graph mapping on inference hardware.
  • Prototype new compilation techniques, including graph transformations and memory optimizations.
  • Collaborate with hardware architects to influence future system designs based on software insights.

What we're looking for

  • MS or PhD in Computer Science or related field with 5+ years of relevant experience.
  • Proficiency in C/C++ and/or Rust, strong software engineering background, and solid CS fundamentals.
  • Hands-on experience with compiler or runtime development, including IR design and optimization passes.
  • Experience with LLVM and MLIR, building custom passes, dialects, and integrations.
  • Familiarity with deep learning frameworks like TensorFlow and PyTorch, and portable graph formats such as ONNX.
  • Solid understanding of parallel and heterogeneous compute architectures, including GPUs and spatial accelerators.

Market check

Salary context

This $152,000–$241,500 range sits above 40% of similar postings on FindRole.

Peer median band

$161,700–$257,100

Median floor and ceiling across peers.

Typical midpoint (25–75%)

$177,875–$238,250

Middle half of comparable postings.

Based on 240 comparable postings.

* 240 is the maximum number of comparable postings sampled.

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 802 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 798 roles with salary data.

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