Principal Data Flywheel Engineer for Autonomous Driving ML

Neolix; Sunnyvale (CA); Presencial; USD 180.000 - 240.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity

Premium health insurance

401(k)

Descripción de la vacante

NeolixUS in Silicon Valley is seeking a hands-on technical leader to build the data flywheel that connects fleet experience to model improvement. You will own the mining-to-training data platform and enable scalable, reproducible datasets for driving models.

This role combines distributed systems, applied ML and dataset science to accelerate model improvement per unit of usable experience, not merely storage.

Formación

• Must have hands-on ownership of scalable distributed data systems or ML data infrastructure.
• Experience with multimodal or sequential datasets and ML workflows.
• Proven leadership across ML, infrastructure and production teams.

Responsabilidades

• Architect a petabyte-scale discovery platform across video, images, crops, sensor context, model outputs and metadata.
• Define cloud-side trigger framework and prioritize informative long-tail scenarios within bandwidth/storage limits.
• Create version-controlled pipelines for discovery, collection, annotation, QA, deduplication, curation and publication.
• Deliver deterministic, high-throughput training data mixtures for end-to-end driving models.
• Turn model weaknesses into mining priorities and prove improvements with controlled comparisons.
• Set architecture and interfaces across regional data teams and uphold privacy and data locality.

Conocimientos

Python

C++

Go

SQL

Data modeling

Descripción del empleo

NeolixUS in Silicon Valley is seeking a hands-on technical leader to build the data flywheel that connects fleet experience to model improvement. You will own the mining-to-training data platform and enable scalable, reproducible datasets for driving models.

This role combines distributed systems, applied ML and dataset science to accelerate model improvement per unit of usable experience, not merely storage.