Director, Applied AI & Data Science

Vantor • Herndon, VA

21h • $182,000 - $266,200

About The Position

Vantor is seeking a Director, Applied AI & Data Science to lead its Applied AI Science organization and deliver deployable AI capabilities with measurable customer, product, operational, and business impact. The role leads and develops Applied AI Scientists working across geospatial AI, multimodal learning, vision-language models, LLMs, reasoning systems, predictive modeling, and production machine learning. It defines the Applied AI Science roadmap and guides the development and productionization of AI applications that turn geospatial, imagery, structured, and contextual data into actionable insights and decision intelligence.

The Director will champion safe and auditable agentic AI adoption to accelerate scientific and engineering workflows, and will develop near-zero-latency intelligence systems that detect and communicate important signals with minimal delay. The role establishes company-wide standards for experimentation, causal reasoning, model evaluation, and launch readiness; oversees end-to-end AI/ML pipelines and production operations; and partners across functions to prioritize investments and advise leaders on AI-enabled products. Applicants must be U.S. citizens and eligible to obtain a security clearance. The position is incentive eligible. The base pay listed for the Washington, DC metropolitan area is $182,000 to $242,000 to $266,200 annually; pay varies by location and candidate qualifications.

Requirements

• Must be a United States citizen and eligible to obtain a security clearance.
• Master’s or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, or a related technical field.
• At least 10 years of experience in machine learning, applied AI, data science, AI engineering, decision science, or a related technical discipline.
• At least 5 years of experience leading technical teams, including applied scientists, machine learning engineers, AI researchers, data scientists, or comparable technical talent.
• Demonstrated experience building, deploying, and operating production AI/ML systems with measurable customer, product, operational, or business impact.
• Strong technical depth in several areas such as multimodal AI, vision-language models, LLMs, reasoning systems, agentic AI, computer vision, geospatial AI, remote sensing, predictive modeling, causal inference, experimentation, or large-scale ML systems.
• Experience building end-to-end ML systems, including data pipelines, training workflows, evaluation frameworks, scalable inference, model monitoring, and retraining.
• Experience defining experimentation standards, model evaluation frameworks, causal inference approaches, or launch-readiness criteria for AI/ML products.
• Strong understanding of modern AI infrastructure, including cloud-based ML platforms, distributed training, containerized deployment, model serving, dataset versioning, and experiment tracking.

Responsibilities

• Lead, grow, and develop a high-performing team of Applied AI Scientists across geospatial AI, multimodal learning, vision-language models, LLMs, reasoning systems, predictive modeling, and production ML.
• Define and execute the Applied AI Science roadmap, translating customer, market, and mission needs into technical priorities, milestones, and deployable AI capabilities.
• Guide the design and productionization of AI applications that transform geospatial, imagery, structured, and contextual data into actionable insights, predictive signals, and decision intelligence.
• Champion agentic AI adoption to accelerate research, experimentation, evaluation, documentation, code review, and production support.
• Identify and automate high-friction scientific workflows to reduce the time from hypothesis to validated production capability while improving quality and repeatability.
• Establish standards for safe, reliable, and auditable use of AI agents across model development, experimentation, evaluation, and operational workflows.
• Drive a near-zero-latency intelligence culture and build a proactive operating model to identify market, customer, user, geopolitical, and operational signals and emerging opportunities.
• Oversee automated insight-generation systems, self-service intelligence platforms, decision-support tools, and AI-powered workflows for cross-functional teams and executive leadership.
• Establish company-wide standards for experimentation, model evaluation, and evidence-based decision-making across AI, analytics, and product development.
• Provide senior guidance on causal inference, counterfactual analysis, A/B testing, benchmark design, offline model evaluation, human-in-the-loop assessment, and launch readiness.
• Define evaluation criteria for generative, agentic, multimodal, geospatial, predictive, and ML-enabled products to ensure they are reliable, robust, explainable, and production-ready.
• Oversee end-to-end AI/ML pipelines, including data ingestion, preprocessing, feature engineering, training, evaluation, inference, monitoring, and retraining.
• Partner with Engineering to productionize models with clear ownership for deployment, serving, monitoring, incident response, lifecycle management, and continuous improvement.
• Ensure AI systems are scalable, cost-efficient, secure, reliable, reproducible, and operationally resilient on modern cloud infrastructure.
• Use data, experimentation, model performance, customer feedback, and business impact to prioritize the Applied AI Science portfolio.
• Build cross-functional alignment for pivots, including stopping underperforming initiatives, reallocating resources, changing technical direction, or accelerating higher-value opportunities.
• Advise Product, Engineering, Go-to-Market, Customer Success, Research, and executive leaders on evaluation, growth and adoption strategies, and AI product investment decisions.

Benefits

• Robust 401(k) with company match
• Mental health resources
• Student loan repayment assistance
• Adoption reimbursement
• Pet insurance
• Incentive-eligible compensation based on contribution, company performance, and/or individual results

What This Job Offers

• Job Type: Full-time
• Career Level: Director