Principal Applied AI Scientist

Vantor Inc.; United States; On-site; USD 150,000 - 240,000; Full time

Benefits offered by this job

401(k) with company match

Mental health resources

Student loan repayment

Adoption reimbursement

Pet insurance

Job summary

Vantor Inc. is hiring a senior machine learning engineer to design, develop, and deploy AI-driven applications that transform large-scale geospatial data into actionable insights and predictive intelligence.

You will build end-to-end ML pipelines, productionize reasoning models and multimodal systems, and collaborate with product, data, and research teams to deliver scalable Earth AI solutions on modern cloud infrastructure.

Qualifications

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field.
• 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 Vision-language models, Multimodal learning, Reasoning models, Large language models, Computer vision or geospatial AI.

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 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 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.

Skills

Python

ML pipelines

Deep learning

Geospatial AI

VLMs

LLMs

Cloud deployment

Experiment tracking

Education

MS or PhD in CS/ML/AI

Tools

PyTorch

TensorFlow

JAX

Job description

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.

Job Description

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.

Having wide-ranging experience, uses professional concepts and company objectives to resolve complex issues in creative and effective ways. Works on complex issues where analysis of situations or data requires an in-depth evaluation of variable factors. Exercises judgment in selecting methods, techniques and evaluation criteria for obtaining results. Networks with key contacts outside own area of expertise. Determines methods and procedures on new assignments and may begin to coordinate activities of other team members. Typically requires a minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience.

Responsibilities

• Design, develop, and deploy AI-driven applications that transform large-scale geospatial data into actionable insights and predictive intelligence.
• Build andoperate 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.
• Optimizemodels and inference systems for scalability, latency, cost efficiency, and reliability on modern cloud infrastructure.
• Implement andmaintain 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, 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 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, or agentic AI systems.
• Familiarity with Google Cloud Platform (GCP), including large-scale AI/ML infrastructure.
• Experience implementing model monitoring, evaluation pipelines, and automated retraining systems.
• Contributions to open-source AI projects, research publications, or patents.

Pay Transparency: To support pay transparency, Vantor includes salary ranges in all U.S. job postings. Starting pay for this role will fall within the listed range and will be based on factors such as experience, qualifications, skills, location, and market conditions. Candidates who meet the minimum requirements for the role should not expect to receive compensation at the top of the range. The listed range reflects the expected pay for this position, and final offers will be determined based on each candidate's experience, expertise, and alignment with the role.

The base pay for this position within Colorado is: $150,000.00 - $200,000.00 - $220,000.00 annually.

The base pay for this position within New Jersey is: $150,000.00 - $200,000.00 - $220,000.00 annually.

The base pay for this position within Delaware is: $150,000.00 - $200,000.00 - $220,000.00 annually.

The base pay for this position within the Washington, DC metropolitan area is: $165,000.00 - $220,000.00 - $242,000.00 annually.

The base pay for this position within California is: $150,000.00 - $200,000.00 - $220,000.00 annually.

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

Additionally, this position is incentive eligible with a target based on contribution, company performance, and/or individual results achieved; the specific incentive plan and target amount will be determined based on the role and breadth of contributions.

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.

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.