Top AI & Machine Learning Jobs

Supports data science teams by cleaning and preparing structured and unstructured datasets, automating ETL workflows, and developing scalable data pipelines. Uses Python, SQL, big-data frameworks, cloud services, and dashboarding tools to support analytics, modeling, LLM/NLP workflows, and operational data products. Maintains documentation, assists with data governance and visualization, and contributes to mission-focused intelligence solutions in a highly sensitive environment.

Develop scalable data science solutions for large structured and unstructured datasets supporting national security missions. Automate data processing, build machine learning and graph-based capabilities, and integrate LLMs into knowledge management workflows. Translate customer needs into analytical solutions, communicate findings through reports and visualizations, deploy models with engineering teams, and mentor junior data scientists. The role is full-time onsite in Reston, Virginia and requires an active TS/SCI clearance with CI polygraph.

Build AI applications, agents, integrations, and automated workflows that transform technical information into customer documentation. Partner with the Documentation team to use LLMs, agentic AI, and automation to improve content creation, maintenance, publishing, and delivery. Reduce manual effort, increase access to technical knowledge, and identify additional customer-facing workflows where AI can improve efficiency and experience.

Design, develop, and deploy AI-native software products that transform large-scale geospatial data into actionable intelligence. Build multi-agent workflows using orchestration frameworks and large language models, engineer tool-using and self-refining agents, develop data ingestion pipelines, and operate secure, scalable AI systems in production. Apply DevOps, reinforcement feedback mechanisms, and AI-assisted development practices while contributing to engineering standards and documentation.

Leads Vantor’s AI-assisted software engineering strategy and transformation. Designs and prototypes agentic workflows for coding, testing, documentation, code review, and automation; evaluates tools; establishes secure governance; runs pilots; builds adoption networks; measures productivity, quality, risk, and business value; and translates evidence into executive recommendations, roadmaps, and scalable operating patterns.

Lead product vision and execution for an agentic geospatial intelligence platform (Site Sentry). Define roadmap, product requirements, benchmarks, and integrations to enable autonomous intelligence production. Partner with AI researchers, engineers, design, GTM, and customers to deliver autonomous reporting, predictive alerts, persistent monitoring, and enterprise integrations. Drive market strategy, cross-functional alignment, and measure product performance and adoption.

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.

Lead scientific development and validation of advanced computational and agent-based models for Ubiquitous Technical Surveillance (UTS). Collaborate with data scientists and engineers to ensure ML and simulation outputs are scientifically defensible, characterize UTS risks, assess uncertainty, and deliver transition-ready decision-support tools for operational use.

Design, develop, validate, and deploy data-driven models and analytics for national-defense missions. Perform data preparation, feature engineering, statistical and deep-learning modeling, time-series analysis, model validation, explainable AI, and performance benchmarking. Automate ETL and workflows, process structured/unstructured data with big-data/cloud frameworks, support LLM integration, and document and present results to technical and non-technical stakeholders.

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.