Sobre este puesto de Data Scientist - Mapping en Zoox
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
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
