Senior Software Engineer, Evaluation Infrastructure

The Evaluation Algorithms team is responsible for building the algorithms & tooling required to comprehensively evaluate our autonomy system’s performance across all development stages. In this role, you will work closely with the systems & safety teams, responsible for defining the requirements & evaluation criteria, and simulation teams to leverage Waabi World, our highly realistic closed-loop simulation engine built with the latest in generative AI technologies to deliver the evaluation capabilities needed to support the safe development of the next generation of autonomous vehicles!

You will…

• Develop the tooling, infrastructure, and pipelines to support complex statistical analyses of driving performance scale.
• Implement metrics and tags to provide a holistic understanding of model performance and enable the discovery of interesting scenarios for training and evaluation.
• Develop and maintain a high availability query service to enable low-latency analysis and curation over large volumes of metric and tag data
• Work with large datasets from various sources including real world driving as well as Waabi World, our high-fidelity simulator.
• Champion engineering excellence, ensuring high-quality, well structured and tested code.
• Assist in project roadmap planning, prioritisation, and delivery.

Qualifications:

• MS/Bachelors degree with 2+ years of industry experience in Computer Science, Machine Learning and/or similar technical field(s) of study.
• Proficient in Python programming and strong software engineering fundamentals with real-world experience writing high quality, well-structured, and well-tested code.
• Open-minded and collaborative team player with the willingness to help others.
• Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.

Bonus Points:

• Experience in data processing pipelines, ETL pipelines, distributed computing.
• Experience in building highly reliable and scalable web services
• Understanding of cloud job orchestration, monitoring, and instrumentation best-practices.
• Experience in evaluating complex ML models or self-driving software stacks.