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Vantor

Staff Applied AI Engineer

Posted An Hour Ago
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In-Office
Westminster, CO, USA
124K-206K Annually
Senior level
In-Office
Westminster, CO, USA
124K-206K Annually
Senior level
The Staff Applied AI Engineer will develop decision intelligence systems using machine learning and optimization, focusing on improving planning decisions and operational efficiency. Responsibilities include building models for revenue attribution, designing decision-support systems, and ensuring security in AI-driven capabilities.
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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.

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).

Please review the job details below.

We are seeking a hands-on Staff-level Applied AI Engineer to build the next generation of decision intelligence within our mission planning systems. This role focuses on learning from historical mission data, quantifying economic outcomes, and improving planning decisions through optimization and machine learning. You will operate as a roving specialist across our engineering organization, working at the intersection of data, algorithms, and operational systems to unlock measurable business impact.

This is not a generic AI role. You will be solving real-world constrained optimization problems with direct revenue implications.

The next generation MPS system doesn’t just automate—it needs to both think and act. With AI built in, MPS will function as a digital operator capable of scheduling tasks on specific sensors and autonomously managing and optimizing constellations, while keeping human operators in the loop with auditable controls.

Cybersecurity must be engineered in—not bolted on. The system will align to zero trust principles and modern DevSecOps practices to accelerate accreditation and deployment across missions. An open architecture and integrated data layer will enable secure collaboration with allies without sacrificing security.

This system must be cloud-native and capable of operating from anywhere. With remote access and seamless integration across terrestrial and space-based networks, operators will compress satellite tasking cycles from days to minutes while maintaining secure operations (potentially) globally.

What You’ll Do

• Develop models to attribute revenue to individual collection plans • Build counterfactual and simulation frameworks to evaluate alternative strategies • Design decision-support systems used daily by mission planners • Apply optimization, reinforcement learning, and heuristic approaches • Map system complexity and identify efficiency improvements • Rapidly prototype solutions using AI-assisted development tools • Collaborate across engineering, data, and product teams

· Engineer AI-driven capabilities that enable MPS to act as an autonomous or semi-autonomous operator, balancing automation with human-in-the-loop control

· Design and build systems aligned to zero trust and DevSecOps principles, ensuring security is foundational—not an afterthought

· Contribute to open architecture and integrated data layer strategies that enable secure collaboration with partners and allied systems

· Build and deploy cloud-native solutions that enable remote mission operations and dramatically reduce planning cycle times

What Success Looks Like (12–18 Months)

• A decision-support system is actively used by planners in daily operations

· Vantor can quantify revenue at the level of individual collection plans

· Teams can evaluate alternative planning strategies with measurable economic outcomes

· Early-stage learning systems (optimization / RL) are improving planning performance over time

Minimum Qualifications

• 5+ years building data-driven or ML-powered systems • Strong Python or similar programming skills • Experience with optimization, simulation, or decision systems • Ability to work in complex problem spaces • U.S. Citizenship required

· Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Operations Research, Engineering, or a related field

Preferred Qualifications

• Experience with operations research or reinforcement learning • Background in decision science or economics • Experience with simulation environments • Familiarity with geospatial or satellite systems • Experience in mission-critical or ITAR environments

Pay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings.  The successful candidate’s starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range.

● The base pay for this position within Colorado is: $124,000.00 - $206,000.00 annually. 

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

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.

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.

Top Skills

Machine Learning
Optimization
Python
Reinforcement Learning
Simulation
HQ

Vantor Westminster, Colorado, USA Office

1300 W 120th Ave, Westminster, CO, United States, 80234

Vantor Colorado Springs, Colorado, USA Office

1975 Research Parkway, Suite 315 , Colorado Springs, CO, United States, 80920

Vantor Denver, Colorado, USA Office

Denver, CO, United States

Vantor Longmont, Colorado, USA Office

1601 Dry Creek Drive, Longmont, CO, United States, 80503

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