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Applied AI Scientist

🕒 vor 2 Monaten

🇺🇸 Vereinigte Staaten – Remote

💵 $128.000 - $215.600 / Jahr

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

🧠 KI-Forscher

🗣️🇺🇸🇬🇧 Englisch erforderlich

Woher diese Stelle stammt

Veröffentlicht auf der Karriereseite von Vantor, nicht über eine Jobbörse

Von Remote Rocketship zum ersten Mal gesehen vor 2 Monaten

Noch offen auf der Website von Vantor. Geprüft vor 6 Stunden.

Logo of Vantor

Vantor

1001 - 5000 Mitarbeiter

🎖️ Verteidigung

📦 Logistik

💼 Beratung

Defense • Logistics • Consulting

Vantor ist ein Unternehmen für räumliche Intelligenz, das einen AI-fähigen "lebendigen Globus" und eine kommerzielle Imaging-Satellitenkonstellation entwickelt, um Sensordaten aus Weltraum, Luft und Boden zu vereinheitlichen. Es bietet Software-Plattformen und Produkte für Echtzeit-Aufgaben, Sensororchestrierung, hochauflösende Basiskarten, Radar- und optische Bilder sowie autonome ISR-Fähigkeiten, die von Verteidigungs-, Geheimdienst-, Regierungs- und Geschäftskunden genutzt werden.

Beschreibung

• Design, develop, and deploy AI-driven applications that transform large-scale geospatial data into actionable insights and predictive intelligence • Build and operate end-to-end AI/ML pipelines covering data ingestion, preprocessing, feature engineering, training, evaluation, and production inference • Productionize reasoning models, vision-language models, and multimodal AI systems combining imagery, geospatial signals, and structured data • Architect enterprise-grade training and experimentation frameworks with automated pipelines, experiment tracking, benchmarking, and reproducible evaluation • Create synthetic datasets and test harnesses to validate model performance, robustness, and edge-case behavior • Collaborate with domain experts, software engineers, product managers, and research partners to translate Earth intelligence challenges into deployable AI solutions • Optimize models and inference systems for scalability, latency, cost efficiency, and reliability on modern cloud infrastructure • Implement and maintain production inference systems, including monitoring, model versioning, retraining workflows, and performance tracking • Stay current with advances in foundation models, generative AI, multimodal learning, and reasoning systems, translating research breakthroughs into practical systems • Maintain engineering standards through code reviews, documentation, experimentation discipline, and collaborative problem solving • Help shape next-generation Earth AI capabilities through collaboration with research organizations and technology partners

🎯 Anforderungen

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field, or equivalent practical experience • 5+ years of experience building and deploying machine learning systems in production environments • Experience designing and delivering end-to-end ML pipelines, including data processing, training automation, evaluation frameworks, and scalable inference • Hands-on experience developing and deploying deep learning models in vision-language models, multimodal learning, reasoning models, large language models, computer vision, or geospatial AI • Strong programming skills in Python • Experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX • Experience building reproducible experimentation pipelines, including model evaluation, dataset versioning, and experiment tracking • Experience deploying models into production environments using modern cloud infrastructure and containerized systems • Familiarity with distributed training, large-scale data processing, and model optimization techniques • Ability to collaborate across research, engineering, and product teams • Must be a U.S. Person: U.S. citizen, permanent resident, Asylee, or Refugee • Preferred: experience 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 (GCP), including large-scale AI/ML infrastructure • Preferred: experience implementing model monitoring, evaluation pipelines, and automated retraining systems • Preferred: contributions to open-source AI projects, research publications, or patents

🏖️ Vorteile

• Robust 401(k) with company match • Mental health resources • Student loan repayment assistance • Adoption reimbursement • Pet insurance • Incentive eligibility with a target based on contribution, company performance, and/or individual results achieved • Inclusive workplace • Reasonable accommodations for applicants with disabilities

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