Multimodal Data Engineer

What you'll do

• Assess project feasibility and define execution plans, quality specifications, resources, and acceptance criteria.
• Own technical delivery from scoping through handoff, coordinating engineers, annotation teams, and vendors.
• Build and improve scalable data pipelines, quality controls, infrastructure, and internal tools.

What they ask for

• 3+ years of experience in data engineering or large-scale data systems, with hands-on ownership of production data workflows.
• Experience delivering datasets or data systems end to end, including scope, timeline, quality, cost, and acceptance criteria.
• Hands-on experience with at least two data modalities, such as text, images, audio, video, or 3D point clouds.
• Experience with large-scale pipelines using distributed processing tools, orchestration tools, cloud object storage, and containerized batch compute.

Nice to have

• Experience preparing pretraining, supervised fine-tuning, RLHF, or evaluation datasets for LLMs or multimodal foundation models.
• Experience with autonomous driving, robotics, embodied AI, or other sensor-based data.

Pay

$120,000 – $225,000 USD annually (base salary)

Tools

Spark, Ray, Flink, Airflow, Dagster, Argo

AI focus

Supports AI data workflows, including preparing datasets for foundation models; preferred work includes pretraining, supervised fine-tuning, RLHF, evaluation, and model-assisted quality control.