Distributed Spectrum

Distributed Spectrum

SkillBridge - Mission Operations Engineer

New York City · Internship

Work authorization requiredDetected 78 days ago
RESTMachine LearningCustomer SupportEmbedded SystemsResearchCommunicationAdaptability

About the role

  • We collect radio data from all over the world, train neural networks to decipher it, and run them on the smallest chips we can.
  • You'll fit in if you want to come to work for the problem itself and don't want to choose between technical rigor, business value, and real-world impact.
  • We work with high ownership and trust, and we do it together in the office 5 days/week.

Responsibilities

  • DS creates systems that power the next generation of radio spectrum intelligence.
  • We're solving a new, technically hard problem where nothing from other fields works out of the box, and along the way, we've built our own stack from scratch, including entirely new embedding model architectures, custom GPU kernels, and much more.
  • Support preparation and execution for field deployments, mission events, test activities, exercises, and customer-facing demonstrations
  • Help document issues, improve deployment procedures, and contribute to checklists, quick-reference guides, training materials, and after-action deliverables
  • Shadow and support personnel working with technical teams, customers, and operators across deployment, validation, and mission-support workflows
  • Mission systems, mission support, deployment engineering, or field engineering

Compensation

  • 401(k) match - up to 4% of your salary

Benefits

  • Above-market salary, equity, and benefits package.
  • Early Series A Equity
  • Excellent health, dental, and vision coverage

Company info

  • Contribute to the connective work between operators, customers, systems, and engineering teams that helps mission outcomes improve over time

Visa & Work Authorization

  • citizen, lawful permanent resident of the U

This listing is sourced directly from Distributed Spectrum's careers page and normalized into a canonical job model.