Senior Deep Learning Compiler Engineer - PyTorch at NVIDIA

Helsinki, South Finland, Finland

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

Bachelor's, Master's, or Ph.D. in Computer Science or a related technical field (or equivalent experience)
8+ years of relevant work experience
Strong command of Python and experience building complex, well-tested software systems
Hands-on experience with deep learning frameworks like PyTorch or JAX, understanding model building and performance challenges
Solid foundation in compiler concepts such as abstract syntax trees (ASTs), intermediate representations (e.g., SSA form), program analysis, and code generation
Excellent communication and collaboration skills for working in a distributed, open-source environment

Responsibilities

Lead the design, implementation, optimization, and maintenance of core compiler technologies that accelerate massive deep learning workloads
Collaborate with engineers who built PyTorch for NVIDIA hardware to pioneer new features and stay at the forefront of framework development
Perform deep performance analysis on workloads running on thousands of GPUs to identify optimization opportunities and shape the future design of Thunder
Work closely with leading compiler, library, and systems teams (e.g., nvFuser, TVM, XLA, CUDA) to translate research into practical, high-impact open-source solutions

Skills

Key technologies and capabilities for this role

PyTorchTorchDynamoTorchInductorCUDAnvFuserTVMXLADeep LearningCompilerGPUPerformance Optimization

Questions & Answers

Common questions about this position

What experience level is required for this Senior Deep Learning Compiler Engineer role?

The position requires 8+ years of relevant work experience, along with a Bachelor’s, Master’s, or Ph.D. in Computer Science or a related field (or equivalent experience).

What key technical skills are needed for this position?

Candidates need a strong command of Python for building complex software systems, hands-on experience with deep learning frameworks like PyTorch or JAX, and a solid foundation in compiler concepts such as ASTs, intermediate representations (e.g., SSA form), program analysis, and code generation.

What soft skills are important for this role?

Excellent communication and collaboration skills are essential, particularly for working effectively in a fast-paced, distributed, open-source environment.

What is the company culture like for this team at NVIDIA?

The team is collaborative, innovative, and fast-paced, involving close work with leading experts in compilers, libraries, and systems in a vibrant open-source ecosystem.

What makes a candidate stand out for this Senior Deep Learning Compiler Engineer position?

Candidates stand out with previous contributions to deep learning compiler projects like TVM, MLIR, or IREE, or deep learning frameworks, and deep expertise in PyTorch internals, particularly its compiler stack.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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