Jobs at Vantor

Develop and maintain model-based systems engineering architectures for a U.S. Space Force system-of-systems enterprise. Use Cameo and related digital engineering tools to manage requirements, traceability, system models, technical specifications, and architecture. Support integration, testing, deployment, sustainment, risk mitigation, and lifecycle planning. Maintain technical documentation and repositories, collaborate with government and contractor stakeholders, and produce engineering reports and decision-support materials.

Develops and integrates digital models, system architectures, technical specifications, interface control documents, and requirements for space sensing missions. Performs systems engineering analysis, design tradeoff evaluation, requirements verification, design review support, and technical risk resolution using MBSE methods and digital engineering tools. Collaborates with government customers, FFRDCs, contractors, and multidisciplinary teams supporting Missile Warning, TISR, and Environmental Monitoring capabilities.

Develops and integrates model-based systems engineering products for a Medium Earth Orbit space and ground system. Responsibilities include defining architectures, technical specifications, and interfaces; supporting design reviews and requirements verification; resolving integration issues; assessing technical risks; preparing recommendations; collaborating with government stakeholders; and mentoring systems engineering teammates.

Develop and execute integration plans for space and ground systems supporting Environmental Monitoring capabilities for the U.S. Space Force. Lead integration across system-of-systems, system, segment, and element levels; research requirements, technologies, and threats; and integrate remote sensing systems. Responsibilities include requirements verification, interface control documentation, technical performance monitoring, test reporting, contractor coordination, and resolving schedule, cost, and risk issues across satellite programs.

Manage technical baselines for complex space sensing programs supporting Missile Warning, TISR, and Environmental Monitoring. Develop and maintain requirements, interface control documents, architectural designs, and MBSE products. Lead requirements and interface management, design reviews, technical evaluations, verification activities, and configuration control. Analyze technical issues, advise program leaders, coordinate stakeholders, and present recommendations to government and corporate partners, including the U.S. Space Force.

Tests, analyzes, evaluates, verifies, and validates complex space and ground systems supporting missile warning, TISR, and environmental monitoring. Plans and executes developmental test and evaluation activities, develops TEMPs, test plans, verification plans, and reports, performs data analysis, and assesses system readiness. The role decomposes requirements, defines test criteria, leads integrated test teams and review boards, supports space-to-ground integration, and collaborates with government, contractors, and test organizations.

Lead project execution for resilient Missile Warning and remote-sensing capabilities supporting the U.S. Space Force. Coordinate technical teams, stakeholders, testing, analysis, evaluation, validation, and verification activities. Manage cost, schedule, performance, and programmatic risks while aligning requirements and driving mitigation. The role requires DoD acquisition experience, cross-functional communication, and regular onsite work two to three days per week or more as needed.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Supports AI engineering initiatives at Vantor, contributing to spatial intelligence solutions and helping develop technologies that enable customers to understand current and future conditions. The posting provides limited role-specific responsibilities but emphasizes problem-solving, innovation, collaboration, and mission-focused work. Applicants must qualify as a U.S. Person under applicable export control and ITAR requirements.

Leads development of statistical and machine learning models for time-series, geospatial, kinematic, and radar data. Responsibilities include feature engineering, forecasting, anomaly detection, data integration, ETL, visualization, algorithm evaluation, simulation, dataset creation, and stakeholder communication. The role also contributes to mission-focused software applications, APIs, data pipelines, documentation, code reviews, and agile development while requiring an active Top Secret or CBP/DHS suitability clearance.

Lead the development of statistical and machine learning models for time-series and geospatial data. Build analytic solutions, datasets, ETL workflows, forecasting and anomaly-detection models, simulations, visualizations, and reports. Evaluate algorithm performance, optimize classifiers, document processes, and collaborate with engineers, analysts, mission partners, and stakeholders to deliver reliable mission-focused software and data capabilities.

Lead and contribute to the design, integration, deployment, and sustainment of mission-focused systems. Translate stakeholder needs into technical requirements, architectures, interface definitions, deployment patterns, and operational processes. Partner with software engineers and data scientists to integrate applications, data pipelines, infrastructure, and external systems. Support testing, verification, troubleshooting, operational readiness, documentation, and reliability improvements for secure, scalable, data-intensive systems.

Develops statistical and machine learning models for kinematic behavior detection using live, historical, time-series, and geospatial data. Responsibilities include data integration, ETL, feature engineering, forecasting, anomaly detection, algorithm evaluation, simulation, visualization, reporting, documentation, and stakeholder collaboration. The role also contributes to mission-focused software applications, APIs, data workflows, code reviews, troubleshooting, and agile development in a remote-first environment.

Lead development of statistical and machine learning models for time-series, geospatial, kinematic, and radar data. Build analytic solutions, training datasets, ETL workflows, forecasting and anomaly-detection models, simulations, visualizations, and performance metrics. Integrate multi-source sensor data, enhance algorithms, document processes, and collaborate with engineers, analysts, mission partners, and stakeholders in an agile environment.

Design, develop, and productionize multimodal AI systems (VLMs, reasoning models, LLMs) for geospatial data. Build end-to-end ML pipelines, experimentation frameworks, synthetic datasets, and scalable inference on cloud infrastructure while collaborating with research, engineering, and product teams.

Design, develop, and productionize multimodal AI systems (VLMs, LLMs, reasoning models) and end-to-end ML pipelines for geospatial data. Build training/experiment frameworks, synthetic datasets, scalable inference, monitoring, and collaborate with research, engineering, and product teams to deliver Earth intelligence solutions.