TS/SCI ML Engineer - Geospatial AI Pipelines

maxar

Herndon (VA)

Vor Ort

USD 165.000 - 215.000

Vollzeit

Vor 6 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Benefits dieser Stelle

401(k) with company match
Mental health resources
Student loan repayment assistance
Adoption reimbursement
Pet insurance

Zusammenfassung

Vantor is seeking a highly skilled engineer to design, develop, and deploy CV pipeline components, including preprocessing and inference engines, for geospatial intelligence applications. You will apply generative AI to GEOINT data, transform data for ML workflows, and push improvements through production-grade pipelines.

Applicants should have 5+ years in programming and ML engineering, strong cloud experience, and familiarity with Kubernetes and CI/CD.

Qualifikationen

  • 5+ years programming experience in Python, TS, Java, or C/C++.
  • 2+ years leading design/architecture of systems.
  • 2+ years in ML/data/backend engineering or related field.
  • Hands-on ML model training, fine-tuning, or adaptation.

Aufgaben

  • Design, develop, and deploy CV pipeline components (preprocessing, training, inference).
  • Implement synthetic data generation using generative AI for GEOINT data.
  • Transform data types for ML/AI workflow stages.
  • Stay updated on CV advances and apply to mission problems.
  • Brief internal teams on progress and results.

Kenntnisse

Python
TypeScript
Java
C/C++
ML engineering
Cloud platforms
Kubernetes
CI/CD

Ausbildung

Bachelor's degree

Tools

Kubernetes
GDAL
Rasterio
GeoPandas

Jobbeschreibung

Vantor is seeking a highly skilled engineer to design, develop, and deploy CV pipeline components, including preprocessing and inference engines, for geospatial intelligence applications. You will apply generative AI to GEOINT data, transform data for ML workflows, and push improvements through production-grade pipelines.

Applicants should have 5+ years in programming and ML engineering, strong cloud experience, and familiarity with Kubernetes and CI/CD.

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