Senior Machine Learning Applications and Compiler Engineer, LPX

Canada

The base salary range is 135,000 CAD - 185,000 CAD for Level 3, and 170,000 CAD - 220,000 CAD for Level 4. · Full-time

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Job details

Pay: The base salary range is 135,000 CAD - 185,000 CAD for Level 3, and 170,000 CAD - 220,000 CAD for Level 4.
Job type: Full-time
Experience: MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 5 years of relevant experience.
Posting language: English
Posted: Sep 28, 2026

Original job description

We are now looking for a Senior Machine Learning Applications and Compiler Engineer!

NVIDIA is 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. This is your chance to be part of something outstandingly innovative!

What You’ll Be Doing

Build, develop, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization.
Define and implement mappings of large-scale inference workloads onto NVIDIA’s systems.
Extend and integrate with NVIDIA’s SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms.
Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware.
Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points.
Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors.
Publish and present technical work on novel compilation approaches for inference and related spatial accelerators at top tier ML, compiler, and computer architecture venues.

What We Need To See

MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 5 years of relevant experience.
Strong software engineering background with proficiency in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency.
Hands on experience with compiler or runtime development, including IR design, optimization passes, or code generation.
Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations.
Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX.
Solid understanding of parallel and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors.
Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements.
Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams.
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.

Ways To Stand Out From The Crowd

Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at scale.
Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas related to performance or scalability.
Demonstrated research impact, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, MICRO, MLSys, NeurIPS, or similar.
Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 135,000 CAD - 185,000 CAD for Level 3, and 170,000 CAD - 220,000 CAD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 27, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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More about this job

Responsibilities

Develop and optimize compiler and runtime components for end-to-end inference, mapping large-scale neural network workloads onto NVIDIA platforms. Benchmark and profile performance, prototype compilation techniques, integrate with NVIDIA’s software ecosystem, and collaborate with hardware teams to inform future architectures.

Requirements

Requires a master’s or doctoral degree in computer science, electrical or computer engineering, or a related field, or equivalent experience, plus five years of relevant experience. Candidates should have strong systems programming skills and experience with compiler or runtime development, LLVM or MLIR, deep learning frameworks, heterogeneous architectures, and performance analysis.

Skills

C/C++
Rust
Compiler Development
Runtime Development
LLVM
MLIR
Deep Learning
TensorFlow
PyTorch
ONNX
Parallel Computing
Heterogeneous Computing
Performance Profiling
Benchmarking
Concurrency
Graph Optimization

Benefits

Equity
Benefits

Visa sponsorship

Not detected in the job text

Keywords

NVIDIA
LPX
Inference
Compiler
Runtime
C/C++
Rust
LLVM
MLIR
TensorFlow
PyTorch
ONNX
Deep Learning
Neural Network Graphs
Graph Transformations
Code Generation
Optimization Passes
Spatial Processors
Dataflow Architectures
Parallel Computing
Heterogeneous Computing
Static Scheduling
Pipeline Parallelism
Tensor Parallelism
Distributed Inference
Performance Modeling
Profiling
Benchmarking
Memory Layout Optimization
Compiler-Hardware Codesign

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