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# Dynamic Scheduler DSP Algorithm Engineer

- **Company:** AST SpaceMobile
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Convex Optimization, Python (Programming Language), MATLAB, Signal Processing, System Testing, Optimization Algorithms, Service Stack
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/dynamic-scheduler-dsp-algorithm-engineer-ast-spacemobile-9003326

## About the Role

* 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.

Physical Requirements

 * Ability to lift up to 25 lbs.
 * Ability to use a computer for extended periods.
 * Ability to work in an office environment, with occasional exposure to lab or test environments to validate algorithms against real system metrics.
 * Ability to travel occasionally to support system validation or cross-team collaboration as needed.

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands.

## Description

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., * 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.


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