Applied AI Scientist

🕒 il y a 2 mois

🏄 California, Colorado, +1 états de plus – Distant

🏄 California – Remote ⛰️ Colorado – Remote 🏖️ New Jersey – Remote

💵 $128 000 - $215 600 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🧠 Chercheur en IA

👻 Score fantôme 12%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Vantor

Site WebLinkedInTous les Emplois

1001 - 5000 employés

🎖️ Défense

📦 Logistique

💼 Conseil

Defense • Logistics • Consulting

Vantor est une entreprise spécialisée en intelligence spatiale qui construit un "globe vivant" prêt pour l'IA et une constellation de satellites d'imagerie commerciale pour unifier les données des capteurs à travers l'espace, l'air et le sol. Elle fournit des plateformes et produits logiciels pour la programmation en temps réel, l'orchestration des capteurs, les cartes de base haute résolution, l'imagerie radar et optique, ainsi que des capacités ISR autonomes utilisées par la défense, le renseignement, le gouvernement et les clients commerciaux.

Description

• 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 • Translate Earth intelligence challenges into deployable AI solutions with domain experts, software engineers, product managers, and research partners • 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 foundation models, generative AI, multimodal learning, and reasoning systems, translating research advances 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

🎯 Exigences

• 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 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 • U.S. Person status required: U.S. citizen, permanent resident, Asylee, or Refugee • Certain roles may be subject to U.S. export control laws requiring U.S. Person status • 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) • Preferred: experience implementing model monitoring, evaluation pipelines, and automated retraining systems • Preferred: contributions to open-source AI projects, research publications, or patents

🏖️ Avantages

• Competitive total rewards package • Robust 401(k) with company match • Mental health resources • Student loan repayment assistance • Adoption reimbursement • Pet insurance • Incentive eligible, with a target based on contribution, company performance, and/or individual results

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