ML Data Engineer — Multimodal AI Pipelines

Veeda AI; Seattle (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

Veeda AI is seeking a senior ML/Data scientist to design, implement, and validate advanced data methods for multimodal world models. You will own the full lifecycle—from problem framing to deployment—building scalable data pipelines and evaluating impact on model performance.

The role emphasizes reproducible software, rigorous experimentation, and collaboration with researchers to advance embodied AI research. Prior publications or strong validation are valued.

Qualifications

• Advanced degree or equivalent hands-on ML research experience.
• Proven ability to develop original ML methods with rigorous validation.
• Experience owning full lifecycle of an ML method from design to deployment.

Responsibilities

• Design, develop, and validate ML methods for data selection, enrichment, annotation, and quality assessment.
• Own the full lifecycle, from problem framing to deployment and continuous improvement.
• Build reliable workflows for processing large-scale real-world datasets and scalable synthetic data pipelines.
• Measure data quality and assess its impact on model performance.
• Use failure analysis and feedback to improve data-processing methods.
• Produce and evaluate labels such as captions, camera poses, depth maps, and segmentation masks.
• Collaborate with researchers and engineers to develop effective data solutions.

Skills

Python

PyTorch

ML methods

Data processing

Experimentation

Software engineering

Education

Master's or Ph.D. in CS/Engineering or related field

Tools

Distributed computing

Job description

Veeda AI is seeking a senior ML/Data scientist to design, implement, and validate advanced data methods for multimodal world models. You will own the full lifecycle—from problem framing to deployment—building scalable data pipelines and evaluating impact on model performance.

The role emphasizes reproducible software, rigorous experimentation, and collaboration with researchers to advance embodied AI research. Prior publications or strong validation are valued.