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Vantor
Vantor
1 001 – 5 000 Darbuotojai
GynybaKonsultavimasLogistika
„Vantor“ yra erdvinės žvalgybos įmonė, kurianti dirbtiniam intelektui parengtą gyvą Žemės rutulio modelį ir komercinių vaizdinimo palydovų žvaigždyną. Jos platformos sujungia iš kosmoso, oro ir antžeminių šaltinių gaunamus jutiklių duomenis, kad būtų galima realiuoju laiku valdyti užduotis, koordinuoti jutiklius, naudoti didelės raiškos bazinius žemėlapius, radarinius ir optinius vaizdus bei autonomines žvalgybos, stebėjimo ir išžvalgymo galimybes. „Vantor“ aptarnauja gynybos, žvalgybos, valdžios institucijų ir komercinius klientus, o jos komandos dirba su palydovinio vaizdinimo, geografinės erdvės duomenų, logistikos ir konsultavimo technologijomis.
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Principal Applied AI Scientist - Vantor, Remote United States

Lead the development of production AI and machine learning systems for Vantor’s spatial intelligence platform. Apply geospatial data, imagery, and multimodal models to generate operational intelligence.

USJungtinės Valstijos
150 000 $ – 220 000 $ / metai
NuotolinisVisas etatasVadovasPrivaloma Kalba: anglųDirbtinio intelekto tyrimų mokslininkasMašininio mokymosi inžinierius
DebesijaGoogle Cloud PlatformNuotoliniai tyrimaiPythonPyTorchTensorFlow

Aprašymas

  • Develop and deploy AI applications that turn large-scale geospatial data into actionable and predictive intelligence.
  • Build and manage complete machine learning pipelines spanning data ingestion, preprocessing, feature engineering, training, evaluation, and production inference.
  • Bring reasoning, vision-language, and multimodal models into production using imagery, geospatial signals, and structured data.
  • Design enterprise training and experimentation frameworks with automated workflows, experiment tracking, benchmarking, and reproducible evaluation.
  • Develop synthetic datasets and testing harnesses to assess model performance, robustness, and edge-case behavior.
  • Work with domain specialists, software engineers, product managers, research collaborators, and technology partners.
  • Improve model and inference performance for scale, latency, cost efficiency, and reliability in modern cloud environments.
  • Maintain production inference systems, including monitoring, model versioning, retraining workflows, and performance measurement.
  • Evaluate developments in foundation models, generative AI, multimodal learning, and reasoning systems for practical application.
  • Uphold engineering quality through code reviews, documentation, disciplined experimentation, and collaborative problem solving.
  • Contribute to the development of next-generation Earth AI capabilities.

Reikalavimai

  • Must hold U.S. Person status as a U.S. citizen, permanent resident, Asylee, or Refugee.
  • Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical discipline, or equivalent practical experience.
  • At least five years of experience building and deploying machine learning systems in production.
  • Experience designing and delivering end-to-end machine learning pipelines.
  • Experience developing and deploying deep learning models.
  • Experience with vision-language models, multimodal learning, reasoning models, large language models, computer vision, or geospatial AI.
  • Advanced Python programming skills.
  • Experience with PyTorch, TensorFlow, or JAX.
  • Experience creating reproducible experimentation pipelines.
  • Experience deploying models with modern cloud infrastructure and containerized systems.
  • Familiarity with distributed training, large-scale data processing, and model optimization methods.
  • Ability to work effectively across research, engineering, and product teams.
  • Typically requires eight years of related experience with a bachelor’s degree, six years with a master’s degree, or three years with a PhD, or equivalent experience.
  • Preferred experience working with geospatial data, remote sensing, satellite imagery, or Earth observation systems.
  • Preferred experience building or fine-tuning foundation models, multimodal models, or agentic AI systems.
  • Preferred familiarity with Google Cloud Platform.
  • Preferred experience implementing model monitoring, evaluation pipelines, and automated retraining systems.
  • Preferred contributions to open-source AI projects, research publications, or patents.

Privalumai

  • 401(k) plan with company matching contributions.
  • Mental health support resources.
  • Student loan repayment assistance.
  • Adoption reimbursement.
  • Pet insurance.
  • Eligibility for incentive compensation based on contribution, company performance, and individual results.

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