NVIDIA

Senior Deep Learning Software Engineer

Santa Clara, California, United States

Not SpecifiedCompensation
Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Computer Hardware, Artificial Intelligence, Software DevelopmentIndustries

Senior Deep Learning Software Engineer

Employment Type: Full-time Location Type: Hybrid

Position Overview

We are seeking a Senior Deep Learning Software Engineer to design and build our automated inference and deployment solution. This role is instrumental in defining a scalable architecture for Deep Learning (DL) inference, focusing on ease-of-use and compute efficiency. Your work will span multiple layers of the DL deployment stack, including developing features in high-level frameworks like PyTorch and JAX, designing and implementing a high-performance execution environment, low-level GPU optimizations, and developing custom GPU kernels in CUDA and/or Triton. This is an exceptional opportunity for passionate software engineers who bridge the boundaries of research and engineering, possessing a strong background in both machine learning fundamentals and software architecture & engineering.

What You'll Be Doing

  • Play a pivotal role in defining a modular, scalable platform to seamlessly bridge training and deployment workflows, enabling tight integration of deployment tooling with training frameworks such as Megatron and Nemo.
  • Leverage and build upon the PyTorch 2.0 ecosystem (TorchDynamo, torch.export, torch.compile, etc.) to analyze and extract standardized model graph representation from arbitrary PyTorch models for our automated deployment solution.
  • Develop support for inference optimization techniques such as speculative decoding and LoRA.
  • Collaborate with teams across NVIDIA to utilize performant kernel implementations within the automated deployment solution.
  • Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities.
  • Continuously innovate on inference performance to ensure NVIDIA's inference software solutions (TRT, TRT-LLM, TRT Model Optimizer) maintain and increase their market leadership.

What We Need to See

  • Master's, 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, with the 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 stack, and the capability to understand and debug end-to-end performance.
  • Familiarity with NVIDIA's deep learning SDKs such as TensorRT.
  • Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Company Information

NVIDIA is increasingly known as "the AI computing company" and is widely considered one of the technology world’s most desirable employers. If you are creative, motivated, and love a challenge, we want to hear from you! Join our model optimization group, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly-growing field.

Salary Range: $184,000 - $356,500 USD (base salary will be determined based on location, experience, and the pay of employees in similar positions). Additional Compensation: Eligible for equity and benefits.

NVIDIA accepts applications on an ongoing basis. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

Skills

Deep Learning
Software Engineering
Automated Inference
Deployment Solutions
Scalable Architecture
PyTorch
JAX
High-Performance Computing
GPU Optimization
CUDA
Triton
Machine Learning
Software Architecture
TorchDynamo
torch.export
torch.compile
Speculative Decoding
LoRA
TRT
TRT-LLM
TRT Model Optimizer

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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