Applied AI Scientist
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Job Description
Applied AI Scientist building production AI systems for Vantor’s spatial intelligence platform. Transforming geospatial data, imagery, and multimodal models into actionable Earth intelligence.
Responsibilities:
- 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
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 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
Benefits:
- 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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