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Lead Software Engineer - Motion Planning

Austin, TX

About the Team

AVRIDE is an autonomous driving company with the mission to make transportation safer and more efficient through cutting-edge technology. We hold a unique position in the market, developing self-driving taxis and delivery robots. Our delivery robot division already has production in the US and Japan. Our team consists of highly talented engineers with extensive expertise. Joining us means diving into a startup atmosphere and making a significant impact on the company's results and the autonomous industry as a whole.

About the Role

As a Lead Software Engineer at Avride, you’ll lead the development of decision-making systems for autonomous vehicles, manage a team of engineers, and build large-scale data and ML pipelines to optimize self-driving behavior in real-world scenarios.

What You'll Do

  • Lead the design, development, and optimization of self-driving car scenarios, ensuring effective obstacle navigation, lane change execution, and decision-making under complex driving conditions.
  • Manage and mentor a team of engineers, establishing efficient workflows, processes, and pipelines to prevent scenario degradation and enhance the quality of the self-driving system.
  • Oversee the collection, labeling, and preprocessing of extensive datasets for machine learning applications, leveraging tools like Toloka, Python, and distributed computing frameworks.
  • Develop and implement machine learning models for classification, motion planning, and decision-making components using Python, PyTorch, Keras, CatBoost, and C++.
  • Architect data pipelines for processing petabyte-scale datasets, optimizing resources in cloud and on-premises environments to ensure high computational efficiency.
  • Design and implement "good driving" metrics, analyze their performance, and continuously improve upon the vehicle's behavioral algorithms.
  • Conduct extensive experiments to identify training targets for improving specific scenarios and optimizing machine learning model performance.
  • Collaborate with cross-functional teams to develop and maintain high-performance data infrastructure using Apache Airflow, NiFi, Hadoop, and Spark.
  • Research and implement state-of-the-art techniques in autonomous driving, ensuring safety and regulatory compliance.

What You'll Need

  • Master's degree in Computer Science, Robotics, or a related field. Foreign equivalent is acceptable.
  • Minimum of 5 years of professional experience in software engineering, machine learning, or robotics.
  • Expertise in programming languages such as Python and C++, with experience in libraries/frameworks like PyTorch, OpenCV, and CatBoost.
  • Proficient in designing and optimizing distributed systems for data processing pipelines
  • Hands-on experience with machine learning workflows, including data collection, labeling, model training, and deployment in production.
  • Deep understanding of autonomous driving components, including motion planning, decision-making algorithms, and sensor data processing.
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes for deploying scalable systems.
  • Proven ability to manage and lead engineering teams, driving innovation and ensuring high-quality deliverables.
  • Experience in creating performance optimization strategies for both hardware and software systems.

Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.

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