NVIDIA Corporation

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

NVIDIA Corporation • $105K — $185K *
US-AnywhereRemote in Toronto, ON
Consumer Technology
Less than 5 years of experience
Reposted Today
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Job Overview by Ladders

Qualifications

  • Pursuing or recently completed MS/PhD in Computer Science, Electrical/Computer Engineering, or related fields.
  • Software engineering experience with C/C++ and/or Rust, and strong foundation in data structures, algorithms, and concurrency.
  • Hands-on experience with compiler or runtime development including IR design and optimization passes.
  • Familiar with LLVM and MLIR, and experienced in building custom passes or dialects.
  • Knowledge of deep learning frameworks like TensorFlow and PyTorch, and portable graph formats such as ONNX.
  • Understanding of parallel/heterogeneous architectures like GPUs or domain-specific processors.
  • Strong analytical skills with proficiency in profiling and benchmarking tools for performance improvements.

Responsibilities

  • Build and maintain high-performance runtime and compiler components focusing on inference optimization.
  • Define and implement mappings of large-scale inference workloads onto NVIDIA's systems.
  • Integrate with NVIDIA's software ecosystem by contributing to libraries and tooling for seamless model deployment.
  • Profile and monitor performance metrics to ensure efficient neural network graph mappings.
  • Collaborate with hardware architects to influence software observations and design future architectures.
  • Prototype and evaluate compilation and runtime techniques tailored to spatial processors.
  • Publish and present technical work at top ML, compiler, and architecture venues.

Benefits

  • Equity participation opportunities.
  • Comprehensive health benefits.
  • Flexible working arrangements.
  • Access to training and development resources.
  • Potential for career advancement within a leading tech company.
Full Job Description
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:
  • Pursuing or recently completed a MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience.
  • Possess software engineering background with familiarity 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.
  • 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 105,000 CAD - 155,000 CAD for Level 2, and 135,000 CAD - 185,000 CAD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 8, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Manufacturing & Automotive
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ
NVDA
* Ladders Estimates

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