Software Engineer, Simulation & Reinforcement Learning

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.