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# Software Engineer, C++ Generalist, AI Systems & Infrastructure

- **Company:** Tesla Motors
- **Location:** Palo Alto, CA, United States
- **Salary:** $140,000.0
- **Contract:** Permanent contract
- **Skills:** Application Frameworks, Software Suite, Computer Vision, C++ (Programming Language), Nvidia CUDA, Computer Engineering, Software Debugging, Linux, Linux on Embedded Systems, Graphics Software, Inter-Process Communication, Machine Learning, Object-Oriented Software Development, OpenCL, Raw Data, Software Engineering, System Software, Image Compression, Data Logging, Multithreading, Information Technology, Build Tools, Hardware Infrastructure
- **Published:** August 1, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17771432?backUrl=%2Fcareer%2F17771432%2FSoftware-Engineer-C-Generalist-Ai-Systems-Infrastructure-California-Palo-Alto

## About the Role

* Experience or familiarity with Computer Vision, Machine Learning & related software conceptsa plus
 * Experience with performant software design, object-oriented C++, compiler design and/or hardcore lower-level C code
 * Proficient developing software on a Linux host, for embedded Linux targets (cross-compilation, etc.)a plus
 * Experience with at least one of the following preferred: imaging software, Cuda/OpenCL, SIMD, multithreading, Linux system software (posix etc.), & computer vision
 * Degree in Computer Science, Physics, Computer Engineering, Electrical Engineering or proof of exceptional skills in related fields with practical software engineering experience, or equivalent experience

## Description

* Write, debug and maintain robust C/C++ code underpinning the entire FSD & Optimus software suite; depending on needs and your interests/skills, you might work on code related to our high frame rate camera & vision stack, design low memory footprint image compression libraries, implement high performance inter-process communication data buffers, improve/extend our image & raw data logging/telemetry code, or make our evaluation/replay software more stable and performant
 * Optimize hardware resources usage, leverage custom hardware components where appropriate
 * Advocate for best coding practices amongst the group, build tools helping engineers to write better code (for instance, performance/memory tracking)
 * Generalize software frameworks when necessary while keeping in mind that too much abstraction can sometimes become a bottleneck


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