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Salary
≈ $114k – $227k per year (Estimated)
Location
Remote (United States)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Sep 3, 2026. Aalyria scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Aalyria is a US technology company headquartered in Livermore, California that supplies laser communications hardware and software-defined networking platforms for networks in motion across land, sea, air and space. Built on technology acquired from Google, its Spacetime platform orchestrates satellite, airborne and terrestrial mesh networks and its Tightbeam product provides free-space optical links for commercial and government customers. It hires software engineers for backend, infrastructure, simulation and optimization systems, research scientists and related technical staff in California, Washington and London.

About Aalyria:

Aalyria is a leading technology company that supplies laser communications technology and temporospatial software-defined networking platforms to the aerospace industry. With technology acquired from Google, Aalyria is at the forefront of innovation in satellite and airborne mesh networks, as well as cislunar and deep-space communications. We are revolutionizing the orchestration and management of planetary mesh networks using any radio or optical spectrum, any orbit, and any hardware across land, sea, air, and space.

Role Overview:

As a Research Scientist, you’ll contribute to state-of-the-art algorithms which advance the most challenging large-scale optimization and resource management problems in communication networks. The successful candidate will join a vibrant and growing research team. This is an applied research role, and you will work with software engineers to integrate research efforts into practical capabilities that can operate at the scale and speed required by Spacetime’s production systems.

Key Responsibilities:

  • Specify, research, design and develop scalable optimization algorithms for large, complex resource allocation problems.
  • Apply techniques from machine learning, integer optimisation, metaheuristic, or other algorithms to improve solution quality and computational efficiency.
  • Collaborate with researchers and engineers to translate research into commercial product capabilities.
  • Evaluate new approaches against realistic problem sizes, constraints, and performance requirements.
  • Publish at leading international conferences and contribute to patent applications.
  • Develop and maintain documentation related to novel algorithms developed by the team.

Required Qualifications:

  • A PhD and/or 3+ years of equivalent research experience in computer science, engineering, mathematics, statistics, or related field.
  • Strong skills in Python and working in Linux environments.
  • A track record of publishing in leading venues such as NeurIPS, ICLR/ICML, INFOCOM/IEEE, SIGCOMM, MobiCom, or ICC/GLOBECOM.
  • Demonstrated ability of working proactively in a self-motivated way.
  • Experience with at least one of:
    • Reinforcement learning/machine learning and associated libraries in Python (e.g. PyTorch, TensorFlow, or JAX).
    • Integer optimisation and associated libraries (e.g. Gurobi, CBC, Google OR tools).
    • Network science, graph theory, geometric deep learning, or representation learning on dynamic graphs (e.g. clustering, temporal GNNs).
    • Metaheuristic algorithms.

Preferred Qualifications:

  • Experience working in the wireless communication, satellite communications and/or software defined networking space.
  • Experience deploying optimization or ML models into production systems with real-time or near-real-time performance constraints.
  • Familiarity with satellite orbital mechanics, RF link budgets, or scheduling problems in constrained networks.
  • Experience with distributed computing frameworks (e.g., Ray, Dask) for scaling optimization or training workloads.
  • Contributions to open-source optimization, ML, or networking libraries.
  • Experience mentoring junior researchers or engineers, or leading small technical workstreams.

What We Offer:

  • Innovative Environment: Work at a cutting-edge company shaping the future of aerospace communications.
  • Impactful Work: Directly contribute to critical national security programs and initiatives.
  • Growth Opportunities: Expand your career with opportunities for professional development and advancement.
  • Inclusive Culture: Be part of a collaborative, supportive, and inclusive workplace where your contributions matter.
  • Flexibility: Flexible working arrangements including hybrid remote/in-office schedules.
  • Compensation and Equity: Competitive salary, comprehensive benefits (401(k), dental, vision, health, life insurance), paid time off, and equity options.

ITAR/EAR Requirements:

This position involves access to export-controlled information. To comply with U.S. government export regulations, applicants must meet one of the following criteria:

(A) Qualify as a U.S. person, which includes:

  • U.S. citizen or national
  • U.S. lawful permanent resident (green card holder)
  • Refugee under 8 U.S.C. 1157
  • Asylee under 8 U.S.C. 1158

(B) Be eligible to access export-controlled information without requiring an export authorization.

(C) Be eligible and reasonably likely to obtain the necessary export authorization from the appropriate U.S. government agency.

The company reserves the right to decline pursuing an export licensing process for legitimate business-related reasons.

Equal Opportunity Employer Statement:

Aalyria is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability status, genetic information, protected veteran status, or any other characteristic protected by law. Qualified applicants from all backgrounds are encouraged to apply.

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