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Aalyria

Machine Learning Engineer - Spacetime UK

Reposted One Month Ago
Hybrid
London, Greater London, England, GBR
Mid level
Hybrid
London, Greater London, England, GBR
Mid level
The Machine Learning Engineer will research algorithms for networking, develop ML infrastructure, maintain documentation, and assist in technical communication.
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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 Machine Learning Engineer, you'll develop and productionise machine learning algorithms related to large-scale optimization and resource management problems in communication networks. The successful candidate will join a vibrant and growing research team, and will work closely with Research Scientists and 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:
  • Research and develop state-of-the-art machine learning algorithms to solve large, complex resource allocation problems.
  • Develop scalable machine learning training infrastructure and manage MLOps tooling.
  • Integrate ML technology with other components of the Spacetime platform to ensure end-to-end functionality.
  • Evaluate new approaches against realistic problem sizes, constraints, and performance requirements.
  • Develop and maintain documentation related to novel algorithms developed by the team.
  • Publish at leading international conferences and contribute to patent applications.


Required Qualifications:
  • Masters or PhD degree in computer science, mathematics, statistics, or other fields related to machine learning.
  • Fluency in Python and at least one deep learning library (e.g. PyTorch, TensorFlow) or mathematical optimization library (e.g. Gurobi, CBC, Google OR tools)
  • Strong technical communication skills.
  • Ability to write clean, maintainable, and efficient code.


Preferred Qualifications:
  • Experience with graph neural networks or reinforcement learning.
  • Experience working in the wireless communication, satellite communications and/or software defined networking space.
  • Experience with distributed computing frameworks (e.g., Ray, Dask) for scaling optimization or training workloads.
  • Experience writing tests for both software and machine learning algorithms.
  • Experience with C or C++
  • Experience with mathematical optimisation and/or metaheuristic algorithms.


What We Offer:
  • Opportunity to lead high-impact, innovative projects in the space technology and digital infrastructure domain.
  • A dynamic, international environment collaborating with leading research centres and industrial partners.
  • Competitive compensation package based on experience.
  • Hybrid working policy with flexible arrangements.
  • Exposure to cutting-edge technologies in space-ground integration, AI-driven networks, and cloud mission control.
Benefits:
  • Competitive salary
  • Pension
  • Health insurance 
  • Equity
Work Requirements & Location:
  • Applicants must have the right to work in the United Kingdom.
  • Work Location: Remote working within the UK.
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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