Applied AI Scientist

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Vantor

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🎖️ Defense

📦 Logistics

💼 Consulting

Defense • Logistics • Consulting

Vantor is a spatial intelligence company that builds an AI-ready "living globe" and a commercial imaging satellite constellation to unify sensor data across space, air, and ground. It provides software platforms and products for real-time tasking, sensor orchestration, high-resolution basemaps, radar and optical imagery, and autonomous ISR capabilities used by defense, intelligence, government, and commercial customers.

📋 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 • 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

🎯 Requirements

• 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

🏖️ Benefits

• 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