Collaborate with ML engineers and data scientists to understand business requirements and design MLOps applications that facilitate effective data operations, reveal data insights, and boost engineers' productivity in ML model training and validation.

Develop the front end of the MLOps applications, for example, a Dataset Management platform that enables ML engineers to curate label data for model training. Another example is the Metrics platform that enables ML engineers to build their own metrics and dashboards to evaluate the performance of their models.

Collaborate with backend engineers and data engineers to integrate seamlessly with data pipelines and workflows on top of modern data processing technologies such as Apache Spark and Airflow, to support the real-time processing and visualization of large-scale data.

Monitor and optimize the performance of the tooling and applications to ensure high availability, scalability, and reliability, to support the development of mission-critical autonomous driving technology.

Continuously define problems and opportunities to iterate the application with a visionary product roadmap that keeps stakeholders on the same page.

Stay up-to-date with the latest trends and technologies in MLOps and data visualization, specifically related to autonomous driving perception and machine learning.

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

5+ years of experience in software engineering and front-end application development.

Experience designing and building modern data-intensive applications such as dashboards for 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.

Knowledge of SQL basics.

Bonus Qualifications

Experience in DevOps or MLOps tooling application development

Experience with Data Pipelines and orchestrators such as Airflow

Experience in ML-related development in the Autonomous Driving industry.

Experience working with distributed data processing platforms such as Databricks.

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 $160,000 to $256,000. 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.

About Zoox

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations

If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

A Final Note:

You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.