We are looking for outstanding Deep Learning Software Engineers to develop and productize NVIDIA's deep learning solutions in autonomous driving vehicles. As a member of our Solution Engineering-Automotive Machine Learning team, you will apply ground breaking NVIDIA deep learning model training/inference software libraries for deployment on NVIDIA's hardware architecture. You will develop new deep learning architectures, train deep learning models, and compile and optimize DNN graphs. As a part of this role, you will be building a close technical relationship with our automotive partners during product development and coordinate with the architecture and software teams to develop the best solution for partners working on our platforms.
What you'll be doing:
Train, fine-tune, optimize and customize perception DNNs in low precision (FP16/INT8)
Apply sophisticated quantization of DNNs
Improve DNN architectures using ML algorithms on NVIDIA GPUs or DLAs
Continuously improve inference speed, accuracy and power consumption of DNNs
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new insights to improve NVIDIA's automotive DNNs.
What we need to see:
MS or PhD degree in computer science, computer vision, computer architecture or equivalent experience in technical field
5+ years of work experience in software development.
2+ years of experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc.)
Experience with solving a computer vision task using deep neural networks, such as object detection, scene parsing, image segmentation.
Strong Python and/or C/C++ programming skills
Proven technical foundation in CPU and GPU architectures, containers (nvidia-docker), numeric libraries, modular software design
Familiar with CNNs and Transformer architectures
Willing to take action and have strong analytical skills.
Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects.
Ways to stand out from the crowd:
Experience with low precision inference, quantization, compression of DNNs
Experience with NVIDIA software libraries such as CUDA and TensorRT
Open source project ownership or contribution, healthy GitHub repositories, guiding and/or mentoring experience
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people in the world working for us. If you're creative and passionate about developing technologies for autonomous driving, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Skills Required
- MS or PhD in computer science, computer vision, computer architecture, or equivalent experience
- 5+ years of software development experience
- 2+ years developing or using deep learning frameworks (PyTorch, JAX, TensorFlow, ONNX, etc.)
- Experience solving computer vision tasks with deep neural networks (object detection, segmentation, scene parsing)
- Strong Python and/or C/C++ programming skills
- Proven technical foundation in CPU and GPU architectures, containers (nvidia-docker), numeric libraries, and modular software design
- Familiarity with CNN and Transformer architectures
- Strong analytical, time-management, and organizational skills
- Experience with low-precision inference, quantization, and model compression
- Experience with NVIDIA software libraries such as CUDA and TensorRT
- Open source project contributions or ownership, active GitHub repositories, and mentoring experience
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
