Senior Deep Learning Software Engineer

We are looking for a Senior Deep Learning Software Engineer to design and build

our automated inference and deployment solution. As part of the team, you will

be instrumental in defining a scalable architecture for DL inference with

emphasis on ease-of-use and compute efficiency. Your work will span multiple

layers of the DL deployment stack, encompassing 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 straddling the boundaries of

research and engineering, with a strong background in both machine learning

fundamentals and software architecture & engineering. What you’ll be doing: Play

a pivotal role in defining of 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 torch 2.0 ecosystem (TorchDynamo, torch.export, torch.compile, etc...)

to analyze and extract standardized model graph representation from arbitrary

torch models for our automated deployment solution. Develop support for

inference optimization techniques such as speculative decoding and LoRA.

Collaborate with teams across NVIDIA to use 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 the inference performance to ensure NVIDIA's inference

software solutions (TRT, TRT-LLM, TRT Model Optimizer) can maintain and increase

its leadership in the market. What we need to see: Masters, PhD, or equivalent

experience in Computer Science, AI, Applied Math, or 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 the

ability to work independently and collaboratively in a fast-paced environment.

Ways to stand out from the crowd: Contributions to PyTorch, JAX, or other

Machine Learning Frameworks. Knowledge of GPU architecture and compilation

stack, and capability of understanding and debugging 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. Increasingly known as “the AI

computing company” and widely considered to be one of the technology world’s

most desirable employers. Are you creative, motivated, and love a challenge? If

so, we want to hear from you! Come, 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. #LI-Hybrid Your base salary will be

determined based on your location, experience, and the pay of employees in

similar positions. The base salary range is 224,000 USD - 356,500 USD. You will

also be eligible for equity and benefits. Applications for this job will be

accepted at least until April 28, 2026. This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to

fostering a diverse work environment and proud to be an equal opportunity

employer. As we highly value diversity in our current and future employees, 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. NVIDIA pioneered accelerated

computing. Today, our AI infrastructure powers global intelligence, transforming

every industry. Learn more about NVIDIA.