Nvidia DRIVE platform offers solutions to build safe, scalable, AI-enabled Autonomous Vehicles. The end‑to‑end full stack platform spans from in‑car supercomputers to cloud‑scale training and simulation. Our goal is to ship cars that continuously learn and improve, bringing the future of self-driving to today’s roads.
We are looking for passionate, AI-powered, engineers for the DRIVE Mapping team. Maps play important roles in localization, routing, and navigation. Maps offer redundancy for live sensor perceptions increasing the safety of the vehicle. In this role, you will help deliver the SD maps to all in-car consumers in the most efficient way. We are seeking the best engineers motivated about solving complex problems for self-driving cars with a background in software design, embedded software, working on real-time software and operating systems. Are you interested in inventing human level AI for navigation in the unconstrained world under any conditions? If so, join us!
What You'll Be Doing:
Design and develop algorithms for map-based driving products
Architecture design for map provider, health monitors and data fusion with perception
Develop highly efficient in-vehicle code in C++14 or later
Design and integrate algorithmic solutions into the core of NVIDIA AV
Research, and develop transformer based models tailored for graphs
Implement evaluation frameworks to measure performance of large scale LLM’s
Analyze and fine-tune SOTA pretrained models on domain specific datasets
Build automated map content analysis in Python, JavaScript or TypeScript
Create scalable and distributed map-building workflows
What We Need To See:
4+ years with BS in Computer Science or equivalent experience
Background in computer vision, 3D geometry and machine learning
Heavy AI user for day‑to‑day development (design, coding, review, and testing)
Hands‑on experience with tools like Claude CLI, Cursor, and other advanced code assistants
Strong prompt‑crafting skills: knows how to break problems down, provide context, and iterate with AI to reach robust solutions
Passion for robotics and autonomous vehicles
Ways To Stand Out From The Crowd:
Prior experience with any navigation maps such as NDS.Live, Open Street Maps (OSM) etc.
Software development on embedded or automotive platforms.
Knowledge of gRPC, Flat Buffers and Protocol Buffers
Experience with GPGPU programming (CUDA)
We believe, realizing self-driving vehicles will be a defining contribution of our generation which can reduce ~1.25 million deaths per year world-wide due to road traffic accidents. We have the funding and the scale, but we need your help on our team. NVIDIA is widely recognized as one of the best places to work. You are invited to do your life’s best work and get surrounded by some of the most forward-thinking and hardworking people in the world!
Skills Required
- 4+ years with BS in Computer Science or equivalent experience
- Background in computer vision, 3D geometry, and machine learning
- Strong prompt-crafting skills for AI solutions
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.”
