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Fullstack Software Engineer - Perception Metrics Platform

AT Zoox
Zoox

Fullstack Software Engineer - Perception Metrics Platform

San Francisco, CA

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.

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In this role, you will:

  • 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.


  • Qualifications

  • 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.
  • Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.


  • Bonus Qualifications

  • Experience with model evaluation and metric frameworks for autonomous driving or machine learning applications.
  • Experience with modern data processing technologies such as Apache Spark, Apache Kafka, and Databricks.
  • Experience with Dash Plotly or related frontend frameworks for data visualization


  • Compensation

    There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $170,000 to $230,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.

    Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

    Client-provided location(s): San Francisco, CA, USA
    Job ID: Zoox-27a32b8c-4e44-4280-8016-4ff68c7b1dde
    Employment Type: Full Time