Data Scientist - Mapping
Zoox
ApplyHigh-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:
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Design and build a high-quality, large-scale mapping dataset and data pipelines for training and evaluating machine learning models
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Design and build tools for model performance benchmarking and introspection
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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.
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Collaborate cross-functionally with a variety of teams working on things such as perception, planning, prediction, simulation, etc
Qualifications:
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BS or MS in Computer Science or a related field and 3+ years of experience
- Experience in computer vision and machine learning algorithms
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Proficient in Python
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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.
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Experience with large-scale, multi-modal datasets, benchmarking and introspection
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Ability to identify, clean, and process datasets containing high levels of noise or ambiguous classifications
Bonus Qualifications:
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Experience with Perception systems
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Knowledge of geospatial data and coordinate systems
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Ability to write highly complex, optimized SQL queries for massive distributed databases
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Databricks experience