---
title: 'Machine Learning Research, RF Foundation Models Specialist at Distributed Spectrum'
canonical: 'https://feeny.ai/job/machine-learning-research-rf-foundation-models-specialist-distributed-spectrum-8asabr0c6qrs'
type: 'job'
last_seen: '2026-09-10'
---

# Machine Learning Research, RF Foundation Models Specialist at Distributed Spectrum

- **Company:** Distributed Spectrum
- **Location:** New York, NY
- **Compensation:** $200k–$300k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-04-24
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/distributed-spectrum/b7ce811d-29bc-4207-af7b-ab6cf5ef428b/application

**Skills:** Modern ML frameworks, Experimental practice, Signal processing, Model optimization, Deployment, RF signal-centric ML, Spectrum sensing, Modulation recognition, Quantization, Kernel-level optimizations

> Join Distributed Spectrum as a Machine Learning Researcher to build AI-enabled sensing systems for radio spectrum intelligence. You will formulate novel ML problems, design experiments, and deploy robust models for structured, noisy signal environments in an onsite New York City role.

## Job description

DS creates systems that power the next generation of radio spectrum intelligence. We collect radio data from all over the world, train neural networks to decipher it, and run them on the smallest chips we can. 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. Joining DS means owning major parts of a fast-growing AI research organization, joining a collaborative, talent-dense team with decades of experience in probabilistic ML, accelerated computing, embedded systems, and signal theory, and growing your career in the areas that interest you. 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.

## About the Role

Some domains already have standard ML playbooks. RF is not one of them. Distributed Spectrum is building AI-enabled sensing systems for the radio domain, and we are hiring a Machine Learning Researcher, Specialist to bring modern ML to a problem space where representation, structure, physics, runtime constraints, and deployment realities all matter at once. This role is designed for a strong generalist researcher who wants genuinely open technical terrain. You will work on problems where signal structure, propagation effects, interference, sparse visibility, and edge deployment constraints all shape what "good" looks like. The job is not just to improve accuracy. It is to formulate the right problem, find the right modeling approach, and get that capability into systems that are used in the field. You will work across the lifecycle of research and deployment: data and evaluation design, experimentation, model development, release readiness, and iteration based on real-world outcomes. You will collaborate closely with embedded, hardware, and mission teammates, and your work will directly influence how Distributed Spectrum builds machine learning capability as the company scales.

## What You'll Do

- Formulate new ML problems in RF sensing and spectrum understanding
- Design experiments and evaluation approaches that reflect real operating conditions including domain shift, changing interference, and varying sensors and platforms
- Build models for structured, noisy, and partially observed signal environments
- Improve robustness across propagation, interference, and low-visibility waveform conditions
- Optimize models for throughput, latency, and deployment constraints
- Move promising research into a release path for real systems through proofs-of-concept, realistic validation, and conversion into maintainable, deployable code
- Use field performance to inform the next generation of models and tooling

## What We're Looking For

- Deep mathematical and modeling fundamentals
- Strong hands-on experience with modern ML frameworks and experimental practice
- Ability to work in domains where problem formulation is as important as implementation
- Strong instincts for signal-rich, structured, non-generic data
- Comfort operating with ambiguity and changing requirements
- Clear technical communication and cross-functional collaboration

Nice-To Haves

- Background in RF or signal-centric ML (spectrum sensing, modulation recognition, or related work) is welcome but not required; we are equally interested in researchers from adjacent domains who have demonstrated strong reasoning on hard signal or sensing problems
- Experience building for constrained inference (quantization, kernel-level optimizations, or similar)
- Evidence of research impact: publications, open-source implementations, or prior work building new architectures that shipped

Who Thrives at Distributed Spectrum

- Fast learners over specific backgrounds – We care more about how quickly you can pick up new skills than where you’ve worked before.
- Intellectual honesty – The right answer matters more than being right. You challenge assumptions, test ideas, and pivot when needed.
- Adaptability – We’re organized, but sometimes things change quickly. You find a way to make it work and balance short-term deliverables with long-term goals.
- Ownership of outcomes – You optimize your own time, focus on what matters to deliver quickly, and cut out inefficiencies.
- Not building in a vacuum – You stay connected to the rest of our teams and our customers to make sure all the pieces fit together.

## What We Offer

- Above-market salary, equity, and benefits package.
- Early Series A Equity
- Excellent health, dental, and vision coverage
- 401(k) match - up to 4% of your salary
- Flexible PTO
- Daily office lunches in NYC

ITAR Requirements

To conform to U.S. Government technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR [here](https://www.pmddtc.state.gov/?id=ddtc_kb_article_page&sys_id=24d528fddbfc930044f9ff621f961987).

## About Distributed Spectrum

## Company Overview
- **One-liner**: Distributed Spectrum builds AI-enabled software and sensors that allow anyone to detect, classify, and understand critical radio signals without requiring expensive hardware or specialized expertise.
- **Entity Type**: Private (Series A)
- **Headquarters**: New York, New York, United States
- **Founded**: 2020
- **Founders**: Alex Wulff, Ben Harpe, Isaac Struhl

## Core Business
- **Primary industry**: Defense technology / Electronic warfare / Signal intelligence
- **Target customers**: Government, defense, and commercial organizations that need real-time spectrum awareness and threat detection
- **Mission or purpose**: “Build AI and sensors to let anyone understand critical radio signals in any mission” – [distributedspectrum.com](https://www.distributedspectrum.com/about)

## Products & Services
- **Detection Mesh**: A network of hot-swappable, off-the-shelf commercial components that creates a vast, AI-powered radio frequency detection system. Provides real-time alerts with unlimited downstream integrations.
- **AI-Enabled Workflows**: Machine learning models that automatically identify and classify signals, enabling operators to act on threats without manual analysis.
- **Deploy Everywhere Platform**: Software that bridges the gap between $100 hardware and legacy $1M+ systems, allowing rapid deployment into existing infrastructure.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Total funding of $25.2M as of April 2025. Series A of $25M, led by Conviction, Shield Capital, and Nat Friedman, with participation from Felicis and XFund. – [linkedin.com](https://www.linkedin.com/company/distributed-spectrum)
- **Notable Investors/Partners**: Conviction, Shield Capital, Nat Friedman, Felicis, XFund, National Science Foundation (grant). Board Director Sarah Guo (Conviction).
- **Growth Signals**: 100% YoY employee growth (32 people), named to American Dynamism 50 in 2025, oversubscribed Series A, strong hiring momentum across engineering and mission operations roles.

## Competitive Advantages
- **Software-first approach**: Shifts focus from expensive proprietary hardware to modular, flexible software running on commercial off-the-shelf (COTS) components.
- **Hard technical moat**: Combines machine learning, embedded systems, and signal processing – a net-new problem space with few competitors.
- **Talent density**: Founders bring deep expertise from Google, Raytheon, Lockheed Martin, Microsoft, Bridgewater; entire team is technical and mission-driven.
- **Speed of deployment**: Can integrate with existing $1M+ systems or run entirely on low-cost hardware, making spectrum monitoring accessible to a wider set of missions.

## Strategic Focus
- **Product expansion**: Scaling the detection mesh and AI workflows to cover more signal types and operational environments (e.g., tactical UAVs, special projects).
- **Hiring for growth**: Actively recruiting for roles in embedded engineering, RF systems, mission operations, and program management to support government and commercial contracts.
- **Go-to-market**: Building out sales and business development teams to penetrate defense and critical infrastructure verticals.

## Why Work Here
- **Culture**: "High growth and high ownership" – trust by default, side-by-side problem solving in the office. Small, elite team where everyone contributes across ML, signal processing, and user design.
- **Work policy**: In-office (New York City). Employees work from physical offices at 147 West 25th Street, 4th Floor, NYC. – [builtin.com](https://builtin.com/company/distributed-spectrum)
- **Engineering culture**: Work on a net-new, technically hard problem with immediate real-world impact in national security. Opportunity to bridge research and production systems.
- **Perks**: Not explicitly listed, but the team is venture-backed and operates with startup intensity – likely standard benefits for a Series A defense tech company.

## Sources
1. [distributedspectrum.com – Home](https://www.distributedspectrum.com/)
2. [distributedspectrum.com – About](https://www.distributedspectrum.com/about)
3. [LinkedIn – Distributed Spectrum](https://www.linkedin.com/company/distributed-spectrum)
4. [Built In – Distributed Spectrum](https://builtin.com/company/distributed-spectrum)
5. [Ashby Careers – Distributed Spectrum](https://jobs.ashbyhq.com/distributed-spectrum)

## Other roles at Distributed Spectrum

- [Operations Associate, Growth](https://feeny.ai/job/operations-associate-growth-distributed-spectrum-new-york-twsse9pdfsyg) — New York, NY
- [Associate Director, Business Development - Army](https://feeny.ai/job/associate-director-business-development-army-distributed-spectrum-new-york-0x6ddj970h79) — New York, NY
- [Mission Operations](https://feeny.ai/job/mission-operations-distributed-spectrum-new-york-2wdwav9ddm8g) — New York, NY
- [RF Systems Engineer](https://feeny.ai/job/rf-systems-engineer-distributed-spectrum-new-york-ft4x6edfd49q) — New York, NY
- [Systems Integration Engineer](https://feeny.ai/job/systems-integration-engineer-distributed-spectrum-new-york-bhf5zsb366jm) — New York, NY
- [Mission Operations Engineer](https://feeny.ai/job/mission-operations-engineer-distributed-spectrum-new-york-v7espz5g5wc0) — New York, NY
- [SkillBridge - Mission Operations Engineer](https://feeny.ai/job/skillbridge-mission-operations-engineer-distributed-spectrum-new-york-x68t58je2nt9) — New York, NY
- [Embedded Engineer](https://feeny.ai/job/embedded-engineer-distributed-spectrum-new-york-2x6w4c797sfm) — New York, NY
- [Growth Department Talent Community](https://feeny.ai/job/growth-department-talent-community-distributed-spectrum-new-york-04c9yc50h0md) — New York, NY