As a Senior Software Developer, you will focus on building and optimizing critical components for motion planning and data analysis. You will work on high-performance systems, develop tools for large-scale simulations, and contribute to machine learning pipelines that improve lane-changing behavior. This role offers the opportunity to tackle complex technical challenges and help shape the future of autonomous driving technology.

• Lead development of the motion planning component, focusing on lane-changing functionalities for self-driving cars.
• Enhance software performance, demonstrating specialized expertise in improving critical components.
• Develop versatile data preparation processes for classification models, adaptable for various tasks with minimal modifications.
• Collaborate across cross-functional teams, including analytics, product management, and QA engineers, to ensure project alignment and optimal performance.
• Optimize data processing systems for self-driving car technology, improving performance and reducing memory usage.
• Using tools like Perf, Heaptrack, and Flame graphs to enhance data component efficiency.
• Establish a distributed service on Kubernetes for complex calculations on remote GPUs, ensuring proper measuring and monitoring systems.
• Enhance the primary framework for data analysis and simulations, increasing speed and effectiveness.
• Utilize advanced data processing technologies such as Spark, SQL, Iceberg, and Argo, in conjunction with Avride's internal tools.
• Develop tools for analyzing road scenes, using SHAP (Shapley Additive exPlanations) to explain model behaviors to the business team.
• Construct a service managing a vast index of over 10 million scenes, enabling quick comparison and analysis of similar scenarios.
• Collaborate with the Quality Assurance team to address feedback from real-city environment tests and simulations.
• Identify and resolve issues within the vehicle's lane-changing process, leveraging comprehensive knowledge of the driving system.
• Recommend solutions to prevent issue recurrence and contribute to ongoing development plans.
• Participate in regular team meetings to discuss and present in-depth reports on the latest research papers in motion planning and prediction.
• Stay current with new scientific developments to guide the team in cutting-edge advancements for self-driving vehicles.
• Conduct thorough code reviews to ensure compatibility with the self-driving car's system, identify logic errors, and suggest performance improvements.
• Provide feedback on organizing new code and avoiding common coding errors, ensuring adherence to company coding standards.
• Apply deep knowledge of programming languages and tools like C++, Python, Spark, Iceberg, and Argo, as well as detailed understanding of the company’s codebase.

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• Master’s degree in Computer Science.
• Proficiency in C++, Python, and their associated frameworks and libraries.
• Familiarity with additional programming languages such as Go, JavaScript, and SQL.
• At least 5 years of professional experience in software development/engineering or equivalent roles.
• Extensive experience with data processing tools and technologies including Spark, SQL, Iceberg, and Argo.
• At least 5 years of experience in developing and deploying machine learning models, including deep learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Strong understanding and experience with high-load systems, including performance optimization and scaling techniques.
• Experience with containerization and orchestration tools such as Docker and Kubernetes, with a focus on deploying and scaling machine learning models in production.
• Proven ability to work with large datasets, including preprocessing, cleaning, and transforming data for machine learning applications.
• Familiarity with well-known algorithms and proficiency in writing complex algorithmic logic for high-performance computing.
• Strong ability to participate in project management activities, set goals and deadlines, and collaborate effectively with other teams in a fast-paced environment.

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