Senior Deep Learning Software Engineer

at Nvidia
📍 Santa Clara, United States
USD 184,000-356,500 per year
SENIOR
✅ Hybrid

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 7 Algorithms @ 7 Machine Learning @ 4 Leadership @ 4 Communication @ 4 Debugging @ 4 LLM @ 4 PyTorch @ 4 CUDA @ 4 GPU @ 4

Details

We are looking for a Senior Deep Learning Software Engineer to design and build an automated inference and deployment solution. The role focuses on defining a scalable architecture for deep learning (DL) inference emphasizing ease-of-use and compute efficiency. Work spans multiple layers of the DL deployment stack: high-level framework features (PyTorch, JAX), high-performance execution environment, low-level GPU optimizations and custom GPU kernels (CUDA and/or Triton). This position sits at the intersection of research and engineering and requires strong ML fundamentals and software architecture & engineering skills.

Responsibilities

  • Define and implement a modular, scalable platform to bridge training and deployment workflows and enable tight integration of deployment tooling with training frameworks (e.g., Megatron, NeMo).
  • Leverage and extend the Torch 2.0 ecosystem (TorchDynamo, torch.export, torch.compile, etc.) to analyze and extract standardized model graph representations from arbitrary torch models for automated deployment.
  • Develop support for inference optimization techniques such as speculative decoding and LoRA.
  • Collaborate with teams across NVIDIA to integrate performant kernel implementations into the automated deployment solution.
  • Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities.
  • Continuously innovate to improve inference performance and help NVIDIA's inference software solutions (TensorRT, TRT-LLM, TRT Model Optimizer) maintain market leadership.

Requirements

  • Masters, PhD, or equivalent experience in Computer Science, AI, Applied Math, or a related field.
  • 8+ years of relevant work or research experience in Deep Learning.
  • Excellent software design skills, including debugging, performance analysis, and test design.
  • Strong proficiency in Python, PyTorch, and related ML tools.
  • Strong algorithms and programming fundamentals.
  • Good written and verbal communication skills and ability to work independently and collaboratively in a fast-paced environment.

Ways to stand out

  • Contributions to PyTorch, JAX, or other machine learning frameworks.
  • Knowledge of GPU architecture and compilation stacks, and ability to understand and debug end-to-end performance.
  • Familiarity with NVIDIA deep learning SDKs such as TensorRT.
  • Prior experience writing high-performance GPU kernels for ML workloads using CUDA, CUTLASS, or Triton.

Compensation & Benefits

  • Base salary ranges (location- and level-dependent):
    • Level 4: 184,000 USD - 287,500 USD per year
    • Level 5: 224,000 USD - 356,500 USD per year
  • Eligible for equity and company benefits.

Location & Other Details

  • Location: Santa Clara, CA, United States. #LI-Hybrid (hybrid work arrangement).
  • Employment type: Full time.
  • Applications accepted at least until July 29, 2025.

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate based on legally protected characteristics.