aipythondata engineeringpytorchstartupdata pipelinesmultimodal dataunstructured datadistributed data processingdataset versioning
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Текст:
Hirify AI/Оригинал
TL;DR
Data Engineer (AI): Building scalable data pipelines that transform raw field logs, sensor streams, and public datasets into curated, versioned, training-ready datasets with an accent on multimodal alignment, data quality, and efficient storage. Focus on designing reproducible dataset workflows, optimizing data delivery for deep-learning training, and solving complex ingestion and curation challenges at terabyte scale.
Location: On-site in Paris, Lausanne, or Zurich
Company
Develops autonomous and scalable defense systems for allied forces, combining mission-critical engineering with deep-learning technology.
What you will do
Ingest, decode, and store raw video and sensor data from field logs in efficient, controlled formats.
Align multimodal data streams temporally and spatially for model training.
Curate field and public datasets through parsing, filtering, de-duplication, and revision.
Define data collection and labeling requirements and own dataset-construction workflows and tooling.
Build task-specific training and evaluation datasets in collaboration with acquisition, annotation, product, and modeling teams.
Implement dataset versioning, lineage, storage tiering, and efficient data loaders to keep training pipelines performant.
Requirements
Degree in a STEM field or equivalent practical experience.
Experience building and maintaining data pipelines for large-scale unstructured video, image, or sensor data.
Strong Python and data engineering skills covering ingestion, decoding, storage, curation, and versioning.
Experience optimizing data loaders for deep-learning frameworks such as PyTorch.
Systematic, quality-minded, pragmatic, and service-oriented approach to automating messy data workflows.
Full commitment to the mission of developing ethical, high-impact defensive technology.
Nice to have
Experience with multimodal sensor data.
Experience with ML labeling or dataset construction.
Familiarity with dataset versioning and distributed data-processing tools.
Culture & Benefits
Work on autonomous defense systems with real-world impact.
Join an early-stage team with meaningful influence over data-processing architecture.
Operate in a demanding environment emphasizing rigor, ownership, execution, and technical excellence.
Collaborate closely with modelers and cross-functional acquisition, annotation, and product teams.
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