Senior Software Engineer - Core-Simulator: Simulation Vehicles

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Senior Software Engineer - Core-Simulator: Simulation Vehicles - s/w focused.

The team is responsible for the primary simulation engine and offline testing framework. They build models for subsystems of the autonomy stack, models for the physical world, and tooling to generate complex scenarios. They build the technology for producing realistic virtual interactions at scale, modeling the physics and behaviors of agents in the world, and gaining and presenting insights about our rich simulation data.The team's goal is to enable rapid development and validation of the autonomy stack through comprehensive offline analysis.

In this role, you will

• Write high-quality, highly testable code in a fast-paced Agile (SRUM) environment using Modern C++ (C++17) and Python.
• Contribute to the development of a scalable and robust vehicle simulation framework and associated tooling.
• Support the development of vehicle simulation fidelity metrics, visualization, and analysis tools. Some prior experience with web backend / front-end technologies is helpful.
• Contribute to data collection tooling and frameworks and the analysis of vehicle track data.
• Evaluate the interaction between perception, planning, control, and vehicle subsystems.
• Support the overall V&V of Aurora Vehicle platforms in simulation.
• Engage with numerous teams across the org and external partners.
• Contribute to engineering best practices in a large and complex code base.
• Example projects that a candidate may contribute to include:
  • Improve computational performance of the vehicle simulation framework
  • Improve code-coverage and suggest architectural improvements that support a loosely-coupled, highlight cohesive design
  • Develop data collection and data pre-processing tools that enable rapid analysis and improvement of vehicle simulation fidelity
  • Investigate and troubleshoot discrepancies that are found between on-road and simulation data
  • Contributing to modeling real world errors in, and testing closed-loop interactions between, planning, localization, mapping, and control subsystems in simulation.

Required Qualifications

• Strong s/w development skills using modern C++ (11, 14, 17, 20)
• Good development skills in Python
• Experience writing high-quality, highly testable code in a fast-paced Agile (SRUM) environment
• Experience using code coverage tools
• Understanding of common software performance issues and design tradeoffs
• Domain experience in simulation, vehicle modeling, controls, motion planning, or other areas of robotics
• BS or higher degree in robotics, computer science, software development, mathematics, or similar technical field of study, or equivalent practical experience
• 5+ years of industry experience designing and programming C++ software
• 5+ years of experience in autonomous vehicles, simulation, robotics, motion planning, localization, controls, computer vision or machine learning

Desirable Qualifications

• Test-Driven and Behavior Driven Development
• Experience with rigid body simulation
• Experience with automotive dynamics
• 5-10+ years of industry experience designing and programming C++ software
• Excellent communication and people engagement skills
• Experience with classical machine learning (ML) algorithms
• Knowledge of linear algebra, computational geometry, or numerical methods
• Experience with Lie groups (modern geometry)
• Experience at an autonomous vehicle company
• Experience writing localization or runtime mapping (i.e. simultaneous localization and mapping, SLAM) software

The base salary range for this position is $168,000-$252,000 per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

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