About Applied Autonomy is one of the leading technological advances of this century that will come to impact our lives. The work you’ll do at Applied will meaningfully accelerate the efforts of the top autonomy teams in the world. At Applied, you will have a unique perspective on the development of cutting-edge technology while working with major players across the industry and the globe.Applied Intuition provides software solutions to safely develop, test, and deploy autonomous vehicles at scale. The company’s suite of simulation, validation, and drive log management software enables development teams to create thousands of scenarios in minutes, run simulations at scale, and verify and validate algorithms for production deployment. Headquartered in Silicon Valley with offices in Detroit, Washington, D.C., Munich, Stockholm, Seoul, and Tokyo, Applied consists of software, robotics, and automotive experts with experiences from top global companies. Leading autonomy programs and 17 of the top 20 global OEMs use Applied’s solutions to bring autonomy to market faster.About The Role We are looking for a software engineer with expertise in computational geometry, simulation, and machine learning. As a software engineer focused on synthetic data and annotations, you’ll build systems to generate labeled data that is suitable for training a variety of machine learning systems. This position will join an existing team of engineers with expertise in computer vision, sensor modeling, rendering, and data infrastructure.At Applied, you will:
- Design and implement core components of our sensor simulation and data generation pipeline
- Develop systems for programmatically generating ground-truth-labeled data from a simulated world
- Work with machine learning pipelines to understand and improve synthetic datasets
- Work with top autonomy companies to understand and solve unique challenges in perception with synthetic data
- Strong software engineering skills in Python and C++
- Familiarity with Unreal Engine
- Competent skills & experience in computational geometry, linear algebra, optics, electro-optics, and physics
- Familiarity with synthetic data and its applications in perception systems
- Experience with applying synthetic data to machine learning tasks
- Detailed knowledge of game pipelines and Unreal Engine
- Hands-on experience with characterization of models for Lidar, Radar, and Camera
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