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Label, annotate, and QA text/image/audio/video datasets per guidelines. Perform random and targeted checks, identify and escalate edge cases, track quality metrics, and provide feedback to annotators to meet productivity and accuracy targets.

Entry-level software engineer for autonomous vehicle systems. Build real-time in-vehicle systems, data transport and logging, communication between embedded devices and hosts, cloud/backend ML infrastructure, model deployment and evaluation, GPU/CPU kernel optimization, and tooling to support developers and large-scale model workflows.

Develop efficient ML solutions for perception including sensor fusion, obstacle detection, scene understanding, and robust onboard systems.

Label and review large text, audio, image, and video datasets to ensure annotation quality and consistency; follow project guidelines, meet targets, and provide process feedback to ML teams.