# Machine Learning Applications and Compiler Engineer, LPX - New College Grad 2026

**Company**: NVIDIA
**Location**: Toronto
**Work arrangement**: remote
**Experience**: entry
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Canada-Toronto/Machine-Learning-Applications-and-Compiler-Engineer--LPX---New-College-Grad-2026_JR2016937?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_8a03fa65-f95

## Description

We are seeking engineers to develop algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads map onto future NVIDIA platforms.

Key responsibilities include:

- Building, developing, and maintaining high-performance runtime and compiler components, focusing on end-to-end inference optimization.

- Defining and implementing mappings of large-scale inference workloads onto NVIDIA's systems.

- Extending and integrating with NVIDIA's SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms.

- Benchmarking, profiling, and monitoring key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware.

- Collaborating closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points.

- Prototyping and evaluating new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors.

- Publishing and presenting technical work on novel compilation approaches for inference and related spatial accelerators at top-tier ML, compiler, and computer architecture venues.

Ideal candidates will have direct experience with MLIR-based compilers or other multilevel IR stacks, especially in the context of graph-based deep learning workloads.

## Skills

### Required
- C/C++
- Rust
- LLVM
- MLIR
- Deep learning frameworks (TensorFlow, PyTorch)
- Portable graph formats (ONNX)
- Parallel and heterogeneous compute architectures (GPUs, spatial accelerators)

### Nice to have
- Prior work on spatial or dataflow architectures
- Contributions to open-source ML frameworks, compilers, or runtime systems
- Research impact (publications, presentations at conferences)

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Canada-Toronto/Machine-Learning-Applications-and-Compiler-Engineer--LPX---New-College-Grad-2026_JR2016937?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)