Used Tools & Technologies
LLMRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Software Development @ 3
TypeScript @ 4
Python @ 4
C @ 4
C++ @ 4
Algorithms @ 4
Machine Learning @ 4
gRPC @ 4
JavaScript @ 4
CUDA @ 4
AI @ 4
Computer Vision @ 4
Robotics @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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. The DRIVE Mapping team delivers HD maps used for localization, routing, and navigation, providing redundancy for live sensor perception to increase vehicle safety.
Responsibilities
- 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 LLMs.
- Analyze and fine-tune state-of-the-art pretrained models on domain-specific datasets.
- Build automated map content analysis in Python, JavaScript or TypeScript.
- Create scalable and distributed map-building workflows.
Requirements
- 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: able to break problems down, provide context, and iterate with AI to reach robust solutions.
- Passion for robotics and autonomous vehicles.
- Experience working on real-time software and operating systems; familiarity with embedded/automotive development practices.
Ways To Stand Out From The Crowd
- Prior experience with navigation maps such as NDS.Live or OpenStreetMap (OSM).
- Software development on embedded or automotive platforms.
- Knowledge of gRPC, FlatBuffers and Protocol Buffers.
- Experience with GPGPU programming (CUDA).
Benefits
- Eligible for equity and company benefits (per posting).
Additional Information
- Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The posting lists base salary ranges by level (see job posting for specifics).
- Applications for this job will be accepted at least until June 14, 2026.
- NVIDIA uses AI tools in its recruiting processes. NVIDIA is an equal opportunity employer and committed to an inclusive work environment.