Director, Applied AI & Data Science

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.

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.

Leadership Profile  

The successful candidate will be:  

Outcome-oriented. Focused on shipping AI capabilities that create measurable customer, product, and business impact.  

AI-native. Energized by using agentic AI to transform how scientific, analytical, and engineering work gets done.  

Technically credible. Able to challenge assumptions, review architectures, guide model strategy, and earn the respect of senior scientists and engineers.  

Experimentation-driven. Skilled at using evidence, causal reasoning, and rigorous evaluation to make better product and technical decisions.  

Operationally disciplined. Able to create systems, rituals, metrics, and accountability mechanisms that improve execution.  

Decisive. Willing to stop low-impact work, redirect resources, and make hard prioritization calls based on evidence.  

Customer-oriented. Able to connect technical decisions to real-world operational value and mission outcomes.  

Collaborative. Comfortable operating across research, product, engineering, infrastructure, sales, customer, and executive teams.  

Responsibilities  

Applied AI Science Leadership  

• Lead, grow, and develop a high-performing team of Applied AI Scientists working 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 ambiguous customer, market, and mission needs into clear technical priorities, measurable milestones, and deployable AI capabilities.  

• Guide the design and productionalization of AI-driven applications that transform large-scale geospatial, imagery, structured, and contextual data into actionable insights, predictive signals, and decision intelligence.  

Agentic AI Adoption & Team Acceleration  

• Champion the adoption of agentic AI as a force multiplier for the Applied AI Science organization, using AI agents to accelerate research, experimentation, evaluation, documentation, code review, and production support.  

• Identify and automate high-friction scientific workflows, reducing cycle time from hypothesis to validated production capability while improving output quality and repeatability.  

• Establish standards for safe, reliable, and auditable use of AI agents across model development, experimentation, evaluation, and operational workflows.  

Near-Zero-Latency Intelligence & Decision Systems  

• Drive the vision for a near-zero-latency intelligence culture, where critical signals are detected, interpreted, and delivered to decision-makers with minimal delay.  

• Build a proactive intelligence operating model that identifies market shifts, customer behavior changes, user behavior trends, geopolitical signals, operational risks, and emerging opportunities before they are visible through traditional reporting.  

• Oversee automated insight-generation systems, self-service intelligence platforms, decision-support tools, and AI-powered workflows that empower Product, Engineering, Sales, Customer Success, Operations, and Executive Leadership.  

Experimentation, Evaluation & Causal Reasoning  

• Establish the company-wide standard for experimentation, model evaluation, and evidence-based decision-making across AI, analytics, and product development.  

• Serve as a senior authority on complex evaluation problems, including causal inference, counterfactual analysis, A/B testing, benchmark design, offline model evaluation, human-in-the-loop assessment, and launch readiness.  

• Define rigorous evaluation criteria for Generative AI, agentic AI, multimodal AI, geospatial models, predictive systems, and ML-enabled product capabilities, ensuring models are reliable, robust, explainable, and fit for production.  

Production ML, Infrastructure & Operational Excellence  

• Oversee end-to-end AI/ML pipelines, including data ingestion, preprocessing, feature engineering, training, evaluation, inference, monitoring, and retraining.  

• Partner with Engineering to move models from prototype to production with clear ownership across deployment, model serving, monitoring, incident response, lifecycle management, and continuous improvement.  

• Ensure AI systems are built for scalability, latency, cost efficiency, security, reliability, reproducibility, and operational resilience on modern cloud infrastructure.  

Portfolio Discipline & Cross-Functional Influence  

• Use data, experimentation results, model performance, customer feedback, and business impact to guide prioritization across the Applied AI Science portfolio.  

• Secure cross-functional alignment for data-driven 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 criteria, growth strategy, adoption strategy, and investment decisions for AI-enabled products.  

Minimum Qualifications

• Must be a United States citizen and eligible to obtain a security clearance.
• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, or a related technical field.  

• 10+ years of experience in machine learning, applied AI, data science, AI engineering, decision science, or a related technical discipline.  

• 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 of the following areas: 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.  

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.

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

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.

To apply, submit your application via Vantor's Career page.

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.