Data Engineer – Autonomous Vehicle

aap3

United States

United States

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Data Engineer with strong AWS + Python/SQL, who builds scalable pipelines for ML training and has experience with large sensor or simulation datasets. Experience Expectations • Expectation on the type of experience. • They want to know if someone with consulting experience who has done small projects at different enterprises is good enough. • Automotive-specific knowledge is not necessarily required. Role Context: Training World Models • The goal is to train world models for autonomous driving applications. • This involves forward prediction models for sensor data. • They need to ingest large amounts of observational real-world data. • They need to bring data into a compute environment to train models. • They need to align the data schema across disparate open source datasets. • The goal is to "bring the data into our compute infrastructure in a way that's usable for research." Data Processing and AWS • The individual will need to do data processing to normalize data into a medium that is compatible with ML training tooling. • This will be done primarily in AWS. • There are any specific AWS tools that are must-haves. • They also ask if they are looking for someone to work with tooling that's agnostic and not necessarily specific to AWS. Tools and Technologies • The tools used are largely AWS tools. • Experience with Azure is not necessary. Data Quality and Schema Enforcement • The research org is not as regimented as some of the more production-oriented AP companies. • The ingestion and cleanup of data is the primary ask. Collaboration and Communication • The idea is to find someone to assist the researchers, freeing them up to focus on model development and architecture. • The researchers would work with the contractor to see what's feasible and useful. • Strong communicator who thrives in ambiguous, research-driven environments, takes ownership of data systems, and collaborates effectively with ML and research teams. Nice-to-have experience includes autonomous vehicle or robotics sensor data, simulation pipelines, ML training data support, dataset versioning, and working closely with research teams.

United States

Sprachkenntnisse

English

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