This listing does not state pay. Across 788 open software engineer listings that state pay, the middle half runs $157,500 to $250,000 and the median is $195,000.

Listed pay is what employers advertise, not what people are paid.

Software Engineer salaries by state · Check your own pay

How AI is used in this kind of work

Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

Check how this applies to your own job

Skills this job asks for

Say which you have and which you want to build. We use it to match you to jobs like this one.

About the job

About Bot Auto

Bot Auto develops autonomous trucking technology. Our Simulation team builds software used to train and evaluate autonomous driving systems.

We are looking for a software engineer with C++ and CUDA experience to develop GPU-accelerated simulation software and improve reinforcement learning training efficiency. You will work with data, planning, and machine learning engineers on simulation and training infrastructure for autonomous trucking.

What You'll Do

Build GPU-accelerated simulation software for autonomous driving and reinforcement learning.

Improve the throughput of parallel simulation workloads and their integration with training workflows.

Profile simulation and training workloads, and optimize CPU and GPU execution, memory usage, and data transfer.

Develop tests and benchmarks to measure correctness, performance, and reproducibility.

Collaborate with data, planning, and machine learning engineers on implementation, design discussions, and code reviews.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or a related field, or equivalent practical experience.

Strong programming skills in C++, including data structures, algorithms, and object-oriented programming.

Experience with CUDA and GPU programming, including an understanding of GPU parallel execution and memory management.

Understanding of parallel and concurrent programming concepts, including multithreading and synchronization.

Familiarity with Python for scripting, testing, or machine learning workflows.

Understanding of reinforcement learning concepts, including environments, agents, actions, rewards, and training workflows.

Experience developing and debugging software in Linux.

Strong problem-solving skills and ability to work collaboratively across teams.

Preferred Qualifications

Experience profiling or optimizing C++ applications, GPU workloads, or machine learning pipelines.

Familiarity with PyTorch or another machine learning framework.

Experience with simulation, robotics, game engines, physics, computational geometry, or high-performance computing.

Experience optimizing GPU kernels or multi-GPU workloads.

Exposure to batched environments, multi-agent systems, or distributed training.

Experience with testing tools, Git, and collaborative software development.