Senior AI Frameworks Engineer

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Santa Clara, CAAustin, TX
Salary: $152,000–$241,500 / yr
Posted: 106 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $210k

This role $197k

$139k most similar roles pay here $276k

This role pays less than 62% of similar roles. Most pay $174,175–$246,150 — the shaded band above. At the midpoint, this role pays about $197k versus about $210k for comparable roles.

Based on 240 similar postings.

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 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior AI Frameworks Engineer

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As a Senior AI Frameworks Engineer on the CUTLASS team, you will work to bridge the gap between low-level hardware primitives and high-level developer productivity by developing Pythonic CUTLASS (CUTLASS DSL). You will be responsible for designing APIs that prioritize user experience for GPU programming, building robust compilation infrastructure including AST transformations and JIT-friendly execution, and creating debugging tools and profiler integrations. Your role involves managing production-grade delivery infrastructure such as package distribution via wheels and conda while maintaining user-facing documentation. To succeed, you must possess expertise in C++, Python, and the design of Python extensions and foreign function interfaces. The work focuses on high-performance math primitives and creating a domain-specific language to lower Pythonic descriptions into high-performance GPU machine code for the open-source community.

Skills

C++ Python CUDA LLVM MLIR JIT AST FFI GPU Programming Conda High-Performance Computing DSL NVIDIA GPU

What you'll do

Design high-level Python APIs to provide a seamless developer experience for GPU programming and kernel delivery.
Develop robust compilation infrastructure including AST transformations and JIT-friendly execution to lower Python descriptions into machine code.
Create tools for debugging, profiler integration, and validation methodologies to simplify the development of kernels.
Build production-grade distribution infrastructure for the open-source community, including wheels and conda packages.
Develop and maintain high-performance C++ and Python extensions using foreign function interfaces (FFI).
Author technical documentation and testing suites for the CUTLASS ecosystem.

What we're looking for

MS or PhD degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
At least 3 years of relevant experience.
Strong proficiency in Python and C++.
Experience designing Python extensions and foreign function interfaces (FFI).
Experience in library or framework development with a focus on intuitive API design for complex systems.
Deep understanding of the Python ecosystem's delivery stack, including building, testing, and distributing high-performance compiled extensions.
Experience with GPU architecture and parallel programming models like CUDA.
Knowledge of compiler foundations, such as intermediate representations (IR), lowering passes, or AST manipulation.