Senior Software Engineer — cuEquivariance

NVIDIA
United States
Workplace: OnsiteFull timeUSD 184,000 - 356,500 annuallyFunction: Software EngineeringExperience: 6+ yearsEducation: mastersSkills: []

Build and optimize CUDA kernels and production-quality GPU-accelerated geometric ML primitives for equivariant neural networks. Own the end-to-end delivery and validation of interfaces that expose cuEquivariance to external frameworks via PyTorch and JAX. Drive multi-GPU CI/CD with correctness and performance regression tracking, and partner with research and third-party teams to translate prototypes into integrated production software.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
NVIDIA
NVIDIA
3 months ago

Senior Software Engineer — cuEquivariance

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 57 minutes agoStatus: Live

Job Summary

Build and optimize CUDA kernels and production-quality GPU-accelerated geometric ML primitives for equivariant neural networks. Own the end-to-end delivery and validation of interfaces that expose cuEquivariance to external frameworks via PyTorch and JAX. Drive multi-GPU CI/CD with correctness and performance regression tracking, and partner with research and third-party teams to translate prototypes into integrated production software.
Location: United States
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Build, implement, and optimize CUDA kernels for equivariant neural network primitives (e.g., tensor products, segmented polynomials, triangle-based operations).
  • •Deliver end-to-end GPU-accelerated geometric ML primitives from implementation through validated, production-quality software.
  • •Build and maintain PyTorch and JAX interfaces that expose cuEquivariance primitives to application developers and researchers.
  • •Develop CI/CD infrastructure for multi-GPU kernel builds, automated correctness testing, and performance regression tracking.
  • •Collaborate with research teams and third-party framework developers to align interfaces and translate prototypes into production kernels.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually
Equity and Bonus:Equity

Key Requirements

  • •6+ years of software engineering experience with a strong background in CUDA and GPU programming.
  • •Deep proficiency in C++ and Python, including experience building and shipping production libraries used by external developers.
  • •Strong GPU fundamentals including memory hierarchy, warp-level execution, occupancy, and performance profiling.
  • •Experience contributing to production scientific software libraries, ML frameworks, or developer-facing GPU APIs.
  • •BS/MS in Computer Science, Physics, Applied Mathematics, or a related field (or equivalent experience).
Experience:6+ yearsMachine learningGPU programmingScientific software
Education:Master's
Tech Stack:CUDAC++PythonGPU programmingPyTorchJAXCI/CDMulti-GPUTritonMixed-precisionTensor coresE3nnMACENequIPSE(3)-TransformersEquivarianceGroup representationsIrreducible representationsTensor products

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
WebsiteLinkedInGlassdoor