Applied AI Scientist

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next.  Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can:
Shape your own future, build the next big thing, and change the world.

To be eligible for this position, you must be a U.S. Person, defined as a U.S. citizen, permanent resident, Asylee, or Refugee.
* Export Control/ITAR:
* Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).
** Please review the job details below.
**** 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
** including data ingestion, preprocessing, feature engineering, training, evaluation, and production inference.
* Productionize
** reasoning models, vision-language models (VLMs), and multimodal AI systems
** that combine imagery, geospatial signals, and structured data.
* Architect
** enterprise-grade training and experimentation frameworks**, including automated pipelines, experiment tracking, benchmarking, and reproducible evaluation.
* Create
** synthetic datasets and test harnesses
** to validate model performance, robustness, and edge-case behavior in real-world operational environments.
* Work closely with
** domain experts, software engineers, product managers, and research partners
** to translate complex 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 the latest advances in
** foundation models, generative AI, multimodal learning, and reasoning systems**, and translate research breakthroughs into practical systems.
* Maintain high engineering standards through
** code reviews, documentation, experimentation discipline, and collaborative problem solving**.
* Help shape the next generation of
** Earth AI capabilities
** through collaboration with leading research organizations and technology partners.
** Minimum Qualifications
*** 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.
* Demonstrated 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**, particularly in one or more of the following areas:
* ** Vision-language models (VLMs)**
* ** Multimodal learning**
* ** Reasoning models**
* ** Large language models (LLMs)**
* ** Computer vision or geospatial AI
*** Strong programming skills in
** Python**, with experience using modern ML frameworks such as
** PyTorch, Tensor Flow, 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
** to bring advanced AI capabilities into real-world applications.
** Preferred Qualifications
*** Experience working with
** geospatial data, remote sensing, satellite imagery, or Earth observation systems**.
* Experience building or fine-tuning
** foundation models, multimodal models,…