Data Scientist - Perception

You will be part of a team building state-of-the-art AI solutions for the Zoox autonomous driving Perception 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 be responsible for designing and building systems to build large dataset and validate models on large (Petabytes) multimodal data. Your work will have a broad impact on shipping high performance ML models by ensuring we have high quality dataset and comprehensive and robust evaluation pipelines. Think you have what it takes to build the best machine learning systems on this planet? Come join us!

• Design and develop our strategy for data development and model evaluation metrics to ensure safe and effective autonomous driving, including defining objective success criteria for ML model deployment 
• Support data-centric AI by: exploring how data impacts ML model performance; guide data labeling strategies; build frameworks for measuring and improving on label quality; develop mining and active learning strategies.
• Define key performance metrics that will help Perception engineers to directly measure the impact of the new features they are developing on the end-to-end driving behavior. 
• Stay up-to-date with the latest developments in machine learning validation techniques and best practices for perception in autonomous vehicles. 

• Bachelor's, Master's or PhD in CS, statistics, mathematics or relevant fields, including statistics (bayesian, parametric statistics, non-parametric, experiment design) and their python-based frameworks (numpy, scipy)
• Experience designing and building evaluation systems for classical and deep-learning models, including linking standard model metrics to end-to-end system behavior and key business metrics
• Experience building and presenting summary metrics to key stakeholders, including advanced knowledge of data visualization techniques
• Experience handling big data, including exposure to distributed data and compute (e.g. Hadoop, Spark, Hive, MapReduce, Databricks), and traditional data query & manipulation (e.g. SQL, NoSQL, Databases)
• Experience adhering to software best practices, e.g. unit testing, DRY, abstraction, modularity, clean interfaces

• Experience building and/or evaluating ML models that operate on raw sensor data (detection, classification, tracking), including ethical AI validation
• Experience in the automotive industry or autonomous driving systems
• Experience with Databricks 
• Knowledge of perception systems or computer vision

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 $169,000-$273,000. 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.