Applied AI Scientist

MAXAR TECHNOLOGIES, INC.; United States; Remote; USD 128,000 - 196,000; Full time

Benefits offered by this job

Robust 401(k) with company match

Mental health resources

Student loan repayment assistance

Adoption reimbursement

Pet insurance

Job summary

Vantor is seeking an experienced AI/ML engineer to design and deploy systems that transform geospatial data into actionable insights. You will build end-to-end ML pipelines, productionize models, and collaborate with researchers and product teams to deliver deployable AI solutions.

The role requires deep learning expertise, strong Python coding, and hands-on experience with cloud deployments and distributed training.

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 Vision-language models, Multimodal learning, Reasoning models, LLMs, Computer vision or geospatial AI.
• Strong programming skills in Python, with experience using frameworks such as PyTorch, TensorFlow, or JAX.
• Experience deploying models into production environments in cloud and containerized setups.
• Familiarity with distributed training and large-scale data processing.

Responsibilities

• Design, develop, and deploy AI-powered applications that transform large-scale geospatial data into actionable insights.
• Build and operate end-to-end ML pipelines including data ingestion, preprocessing, feature engineering, training, evaluation, and production inference.
• Productionize reasoning models and multimodal AI systems combining imagery and data.
• Create scalable experimentation and evaluation frameworks with reproducible workflows.
• Collaborate with researchers, engineers, and product teams to translate Earth intelligence challenges into deployable AI solutions.
• Monitor and optimize models for latency, cost, and reliability in cloud environments.
• Stay current with advances in foundation models and generative AI to inform practical systems.

Skills

Python

ML pipelines

PyTorch

TensorFlow

JAX

Distributed training

Geospatial AI

Education

MS/PhD in CS/ML/AI/Applied Mathematics or related field

Tools

PyTorch

TensorFlow

JAX

Job description

Company Overview

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.

Eligibility

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).

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 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, 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

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: $128,000.00 - $170,000.00 - $187,000.00 annually.
• The base pay for this position within New Jersey is: $128,000.00 - $170,000.00 - $187,000.00 annually.
• The base pay for this position within Delaware is: $128,000.00 - $170,000.00 - $187,000.00 annually.
• The base pay for this position within the Washington, DC metropolitan area is: $140,000.00 - $187,000.00 - $205,700.00 annually.
• The base pay for this position within California is: $147,000.00 - $196,000.00 - $215,600.00 annually.

Benefits

• Robust 401(k) with company match
• Mental health resources
• Student loan repayment assistance
• Adoption reimbursement
• Pet insurance

You can find more information on our benefits at: https://www.Vantor.com/careers

Incentives

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.

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. We also provide reasonable accommodations for applicants with disabilities in compliance with federal and state laws.