Geospatial Ai Jobs in Virginia (NOW HIRING)

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.

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 deployAI-driven applicationsthat transform large-scale geospatial data into actionable insights and predictive intelligence.

• Build andoperateend-to-end AI/ML pipelinesincluding data ingestion, preprocessing, feature engineering, training, evaluation, and production inference.

• Productionizereasoning models, vision-language models (VLMs), and multimodal AI systemsthat combine imagery, geospatial signals, and structured data.

• Architectenterprise-grade training and experimentation frameworks, including automated pipelines, experiment tracking, benchmarking, and reproducible evaluation.

• Createsynthetic datasets and test harnessestovalidatemodel performance, robustness, and edge-case behavior in real-world operational environments.

• Work closely withdomain experts, software engineers, product managers, and research partnersto translate complex Earth intelligence challenges into deployable AI solutions.

• Optimizemodels and inference systems forscalability, latency, cost efficiency, and reliabilityon modern cloud infrastructure.

• Implement andmaintainproduction inference systems, including monitoring, model versioning, retraining workflows, and performance tracking.

• Stay current with the latest advances infoundation models, generative AI, multimodal learning, and reasoning systems, and translate research breakthroughs into practical systems.

• Maintain high engineering standards throughcode reviews, documentation, experimentation discipline, and collaborative problem solving.

• Help shape the next generation ofEarth AI capabilitiesthrough collaboration with leading research organizations and technology partners.

Minimum Qualifications

• MS or PhD inComputer 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 systemsin production environments.

• Demonstrated experience designing and deliveringend-to-end ML pipelines, including data processing, training automation, evaluation frameworks, and scalable inference.

• Hands-on experience developing and deployingdeep 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 inPython, with experience using modern ML frameworks such asPyTorch, TensorFlow, or JAX.

• Experience buildingreproducible experimentation pipelines, including model evaluation, dataset versioning, and experiment tracking.

• Experience deploying models intoproduction environmentsusing modern cloud infrastructure and containerized systems.

• Familiarity withdistributed training, large-scale data processing, and model optimization techniques.

• Ability to collaborate acrossresearch, engineering, and product teamsto bring advanced AI capabilities into real-world applications.

Preferred Qualifications

• Experience working withgeospatial data, remote sensing, satellite imagery, or Earth observation systems.

• Experience building or fine-tuningfoundation models, multimodal models, or agentic AI systems.

• Familiarity withGoogle Cloud Platform (GCP), including large-scale AI/ML infrastructure.

• Experience implementingmodel monitoring, evaluation pipelines, and automated retraining systems.

• Contributions toopen-source AI projects, research publications, or patents.

Pay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings. The successful candidate's starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range.

For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range.

Benefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at:https://www.Vantor.com/careers

The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire.

The date of posting can be found on Vantor's Career page at the top of each job posting.

To apply, submit your application via Vantor's Career page.

EEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.