Data Scientist - Mapping

High-definition HD maps are foundational to enabling safe, scalable autonomous driving. We are seeking highly motivated engineers who are passionate about solving complex, real-world problems and building state-of-the-art mapping systems.

In this role, you will collaborate with a diverse, cross-functional team to design and develop large-scale HD mapping algorithms, workflows, and data pipelines. Your work will directly impact our ability to efficiently map new cities and continuously update existing maps at scale, playing a critical role in accelerating our autonomous vehicle deployment.

In this role, you will:

• Design and build a high-quality, large-scale mapping dataset and data pipelines for training and evaluating machine learning models
• Design and build tools for model performance benchmarking and introspection
• Collaborate closely with machine learning engineers to define and refine data curation and model training strategies that drive measurable improvements in model accuracy and performance.
• Collaborate cross-functionally with a variety of teams working on things such as perception, planning, prediction, simulation, etc

Qualifications:

• BS or MS in Computer Science or a related field and 3+ years of experience
• Experience in computer vision and machine learning algorithms
• Proficient in Python
• Strong Statistical Foundations: Deep understanding of hypothesis testing, experimental design, regression analysis, non-parametric/resampling methods (e.g., bootstrapping, permutation tests), and time-series analysis handling autocorrelated data.
• Experience with large-scale, multi-modal datasets, benchmarking and introspection
• Ability to identify, clean, and process datasets containing high levels of noise or ambiguous classifications

Bonus Qualifications:

• Experience with Perception systems
• Knowledge of geospatial data and coordinate systems
• Ability to write highly complex, optimized SQL queries for massive distributed databases
• Databricks experience

$176,000 - $240,000 a year

Base Salary Range

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.

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 [email protected] 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.