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About the Role

Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.

Responsibilities

Architect and own the scraping and crawling infrastructure that acquires petabytes of image and video data.
Design systems that are resilient, compliant, and able to keep pace with a fast-moving content landscape.
Build and maintain production data pipelines that clean, transform, and process raw visual assets.
Handle format diversity, resolution variance, metadata extraction, and noise at scale.
Design ETL/ELT workflows that prepare image and video datasets for ML model training and evaluation.
Include annotation ingestion, quality scoring, and reproducible dataset versioning.
Continuously profile and optimize pipelines for throughput, latency, and cloud storage/compute costs.
Ensure research velocity without unnecessary overhead.
Select, deploy, and operate distributed data-processing frameworks (e.g., Ray, Spark, Dask) to handle compute-intensive tasks.
Work directly with Computer Vision Engineers, ML Scientists, and product teams to translate data requirements into reliable, well-documented pipelines.
Close the feedback loop between model performance and data quality.
Lead data-pipeline design reviews.
Mentor junior and mid-level data engineers.
Establish best practices for the data team.
Raise the overall engineering bar.

Requirements

5+ years of professional experience in data engineering or a closely related discipline.
Strong foundation in distributed systems, database design, and handling large binary assets (images, video) at scale.
Strong programming skills in Python and SQL.
Proven experience designing end-to-end production systems rather than basic scripts.
Designed and operated web scraping or data ingestion systems running reliably in production at significant global scale.
Hands-on with data-processing frameworks (e.g., PySpark, Pandas, Ray).
Comfortable with image-processing libraries (OpenCV, Pillow, scikit-image).
Built ETL/ELT pipelines for ML/CV use cases with a strong emphasis on dataset provenance, lineage, and reproducibility.
Extensive experience with cloud object storage (AWS S3, GCP GCS).
Understand the cost, latency, and durability trade-offs when managing petabyte-scale data assets.
Daily workflow runs through AI coding harnesses (e.g., AI agents/assistants) without sacrificing software engineering rigor.
Review agent code diffs with the same scrutiny as a team member's PR.
Recognize AI code generation failure modes.
Ship rapidly without introducing technical debt or "slop."

Skills

Python
SQL
Distributed systems
Database design
Large binary asset handling
Web scraping
Data ingestion
PySpark
Pandas
Ray
OpenCV
Pillow
scikit-image
ETL/ELT pipelines
ML/CV use cases
Dataset provenance
Dataset lineage
Dataset reproducibility
AWS S3
GCP GCS
AI coding harnesses
Airflow
Dagster
Prefect
Computer Vision
Image annotation formats
MLOps
Data versioning
DVC
LakeFS
Experiment tracking
Docker
Kubernetes
Data compliance
GDPR
Content licensing
Image rights

Location

Remote

Work Type

Full-time

Experience Level

5+ years of professional experience

About the Company

Veeda AI is building the next generation of multimodal foundation world models for Physical AI.
We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence.