Full Stack Software Engineer, Zoox

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 4+ years of experience in software engineering and front-end application development.
• Experience designing and building modern data-intensive applications such as data warehouses that query and visualize data at a large scale
• Experience with modern web frameworks (e.g. react, angular, vue), python API frameworks (e.g. FastAPI, Django), and writing high-quality backend Python code
• Proficiency in data query languages and tools, e.g. SQL, NoSQL
• Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment

Desirable

• We are seeking a highly skilled Full Stack Engineer to design and develop a metric platform for the Perception component of our autonomous driving stack
• As a member of the Perception team, you will be part of the “eyes and ears” of the Zoox autonomous driving stack, deploying state-of-the-art AI solutions to ensure safe and effective driving
• In this role, you will work closely with data engineers, data scientists, and software engineers to build a scalable and high-performance platform that enables perception engineers to efficiently evaluate their models across petabytes of multimodal data
• You will be responsible for guiding the design of our metrics platform and managing a suite of frontends and APIs that power our platform, ensuring that they follow best practices and increase the efficiency, safety, and accuracy of not only Perception, but Zoox’s autonomous driving stack as a whole
• Develop frontends, APIs, and microservices using technologies such as Python, Plotly Dash, GRPC, Postgres, ElasticSearch, Redis, Kafka, Kubernetes, and AWS, that data scientists and ML engineers can use to effectively generate insights into the performance of autonomous driving perception and machine learning models
• Monitor and optimize the performance of metrics calculations and metrics query access to ensure high availability, scalability, and reliability, to support the development of mission-critical autonomous driving technology
• Collaborate with ML engineers, software engineers, data engineers, and data scientists to understand business requirements and design a scalable and efficient metrics platform that enables perception engineers to build their own metrics and abstracts the complexity of the platform
• Integrate the metrics platform into the organization's CI/CD pipeline, to ensure that metrics are tracked and analyzed throughout the development lifecycle
• Develop frameworks and processes for the metrics lifecycle, including: designing metrics, efficiently implementing metric calculations, comparison and traceability of metrics over time, visualization of metrics and insight
• Stay up-to-date with the latest trends and technologies in data engineering, MLOps, analytics, and visualization, specifically related to autonomous driving perception and machine learning