Dynamic Scheduler DSP Algorithm Engineer

AST SpaceMobile is building the first and only global cellular broadband network in space to operate directly with standard, unmodified mobile devices based on our extensive IP and patent portfolio and designed for both commercial and government applications. Our engineers and space scientists are on a mission to eliminate the connectivity gaps faced by today’s five billion mobile subscribers and finally bring broadband to the billions who remain unconnected.

Position Overview

The Dynamic Scheduler DSP Algorithm Engineer designs and optimizes a resource-allocation algorithm for the satellite payload system, working at the intersection of combinatorial optimization, signal processing, and system-level performance trade-offs. This person designs, analyzes, and improves optimization algorithms for large-scale resource-allocation problems, balancing competing system objectives — efficiency, coverage, and performance — and validating solutions against simulation and real system metrics rather than theoretical guarantees alone. The role requires strong communication skills and comfort working across algorithm, system, and hardware constraints to ensure solutions scale efficiently to large problem sizes. 

Key Responsibilities:

• Design, analyze, and improve optimization algorithms for large-scale resource-allocation problems.
• Balance competing system objectives (efficiency, coverage, performance) and formalize the trade-offs involved.
• Validate algorithms against simulation and real system metrics, not just theoretical guarantees.
• Ensure solutions scale efficiently to large problem sizes.

 Qualifications 

Education:

Experience:

• Strong background in optimization (combinatorial and/or convex), with hands-on problem-solving experience.
• Proficiency in Python or MATLAB for algorithm prototyping.
• Ability to translate mathematical/technical specifications into working code. 

Preferred Qualifications:

• Background in wireless communications, satellite systems, or signal processing.
• Graduate degree (MS/PhD) in EE, applied math, operations research, or CS with an optimization focus. 

Soft Skills:

• Strong communication skills, with the ability to work effectively across algorithm, system, and hardware constraints. 

Technology Stack:

• Python and/or MATLAB for algorithm prototyping.
• Combinatorial and convex optimization frameworks and solvers.
• Simulation and system-metric validation tooling for large-scale resource-allocation problems.