Staff ML Data Engineer for End-to-End Pipelines

Veeda AI; Zürich; On-site; CHF 120,000 - 180,000; Full time

Job summary

Veeda AI seeks a talented ML/Data scientist to own the full lifecycle of data-driven methods. You will design, validate, and deploy ML approaches for large-scale, real-world datasets, including synthetic data generation and annotation tasks.

You will collaborate with researchers and engineers to improve data quality and model performance, applying rigorous experiments and reproducible software practices in a fast-moving environment.

Qualifications

• Master's degree or PhD in CS, Engineering, or related field, or equivalent hands-on experience.
• Proven ability to develop ML methods with rigorous experimental validation.
• Experience owning the full lifecycle of an ML method: design, data application, evaluation, iteration.
• Strong Python and PyTorch skills; ability to train and adapt models.
• Design controlled experiments with meaningful metrics and error analysis.

Responsibilities

• ML methods for data: design, develop, validate data selection, enrichment, annotation, quality assessment.
• End-to-End ownership: from problem formulation through deployment and improvement.
• Large-Scale application: build workflows for large-scale datasets and synthetic data pipelines.
• Evaluation & experimentation: measure data quality and impact on model performance.
• Iterative improvement: use failure analysis to improve data-processing methods.
• Annotation: produce labels such as captions, poses, depth maps, and segmentation masks.
• Research collaboration: partner with researchers and engineers to develop data solutions.

Skills

Python

PyTorch

Experiment design

Data analysis

Software engineering

Education

Master's degree or PhD

Tools

Python

PyTorch

Distributed systems

Job description

Veeda AI seeks a talented ML/Data scientist to own the full lifecycle of data-driven methods. You will design, validate, and deploy ML approaches for large-scale, real-world datasets, including synthetic data generation and annotation tasks.

You will collaborate with researchers and engineers to improve data quality and model performance, applying rigorous experiments and reproducible software practices in a fast-moving environment.