Software Engineer

About The Company

General Motors (GM) is a global leader in automotive manufacturing, committed to innovation, sustainability, and safety. With a rich history spanning over a century, GM continuously pushes the boundaries of technology to shape the future of mobility. The company's vision is to create a world with Zero Crashes, Zero Emissions, and Zero Congestion, leveraging cutting-edge advancements in electric vehicles, autonomous driving, and connected technologies. GM's diverse team of engineers, technologists, and designers work collaboratively to develop solutions that enhance the safety, efficiency, and accessibility of transportation worldwide. As a forward-thinking organization, GM fosters an inclusive environment that values innovation, integrity, and continuous learning, aiming to lead the automotive industry into a new era of mobility.

About The Role

The Smart Agents group at GM is responsible for developing advanced machine learning models and systems that simulate road user behaviors in various scenarios. These simulations are crucial for testing and training autonomous vehicle (AV) driving policies, ensuring safety and reliability before real-world deployment. The team works on creating realistic AI-controlled characters such as other vehicles, bikers, and pedestrians, which interact dynamically within simulation environments—akin to a sophisticated video game. The role involves designing and implementing ML and reinforcement learning (RL) models, optimizing training loops, streamlining system pipelines, and building infrastructure for scalable deployment. Candidates will collaborate closely with Simulation, Behaviors, Perception, and Safety Engineering teams to develop innovative solutions that advance GM's autonomous driving capabilities. Experience in simulation, robotics, and high-performance ML system development is highly desirable, with a focus on creating robust, efficient, and scalable AI models that facilitate rapid experimentation and deployment.

Qualifications

• 4+ years of experience in robotics, simulation, or latency-sensitive backend services
• Proven expertise in machine learning and classification tasks
• Experience with ML frameworks such as TensorFlow or PyTorch
• Strong programming skills in modern C++ and Python
• Experience profiling CPU and GPU software, process scheduling, and optimization
• Ability to design across multiple systems and integrate complex components
• Familiarity with reinforcement learning (RL) and sequence prediction models
• Excellent problem-solving skills with the ability to investigate sophisticated areas
• Strong communication and mentorship abilities

Responsibilities

• Develop and refine machine learning and reinforcement learning models for simulation of road user behaviors
• Create and optimize training loops, data pipelines, and ML infrastructure for scalable deployment
• Collaborate with cross-functional teams including Simulation, Perception, and Safety Engineers to ensure model robustness and realism
• Streamline model training, evaluation, and deployment processes to facilitate rapid experimentation
• Profile and optimize CPU/GPU software to improve system performance and efficiency
• Design and implement scalable system architectures that support high-performance ML pipelines
• Investigate complex technical challenges related to simulation fidelity, system integration, and model accuracy
• Mentor junior team members and contribute to technical strategy and best practices

Benefits

• Competitive salary within the range of $134,000 to $235,900, commensurate with experience
• Performance-based incentive pay
• Comprehensive health and wellbeing benefits including medical, dental, vision coverage
• Health Savings