---
title: 'Senior Embedded Software Engineer - Inference AI/ML at Allen Control Systems'
canonical: 'https://feeny.ai/job/senior-embedded-software-engineer-inference-ai-ml-allen-control-systems-austin-03xr6sqn4246'
type: 'job'
last_seen: '2026-09-09'
---

# Senior Embedded Software Engineer - Inference AI/ML at Allen Control Systems

- **Company:** [Allen Control Systems](https://feeny.ai/companies/allen-control-systems)
- **Location:** Austin, TX
- **Employment:** full-time
- **Posted:** 2026-08-25
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/allen-control-systems/e0e7a1c2-3008-438d-9d24-a49683aca0ad

## Job description

Company Overview ACS (Allen Control Systems) is a defense technology company building precision robotic systems for the United States and its allies. Founded by two former U.S. Navy electrical engineers with deep experience in robotics and software, ACS brings together AI, computer vision, precision motion, and advanced hardware to solve complex defense challenges across land, air, and maritime environments.

Our flagship product, Bullfrog, is an autonomous precision weapon system that transforms existing weapons into highly accurate counter-drone systems — giving warfighters a scalable, cost-effective response to one of the fastest-growing threats on the modern battlefield. Bullfrog is deployed with U.S. forces, and ACS works with organizations throughout the U.S. military and national security community.

Following a $200 million Series B at a $2.2 billion valuation, ACS is rapidly expanding manufacturing, accelerating Bullfrog deployments, and developing the next generation of autonomous battlefield systems. This is an opportunity to join a proven, fast-moving team and help scale technology with direct, real-world impact on national security.

ACS is headquartered in Austin, Texas, with additional operations in Alexandria, Virginia; Mountain View, California; and Huntsville, Alabama. For more information, visit allencontrolsystems.com http://allencontrolsystems.com.

## About The Role

We are looking for a Senior Embedded Software Engineer - Inference AI/ML to own the end-to-end process of taking trained ML models and deploying them efficiently onto resource-constrained edge hardware. This role sits at the intersection of machine learning, embedded systems, and hardware engineering.

You will integrate, convert, and optimize models to run within strict constraints on latency, memory, power, and thermal budget, and build the supporting C++ infrastructure that hosts them on device. You will partner closely with the CV/ML Engineering team who build the models, the Embedded and Firmware teams who own the device, and the product team who define performance targets. Success means models that are not just accurate in the lab but fast, small, and dependable in the field.

## What You’ll Do

- Apply quantization, pruning, knowledge distillation, operator fusion, and graph optimization to shrink models and reduce inference cost while protecting accuracy; convert trained models into edge-deployable formats using ONNX and TensorRT.
- Profile inference on target accelerators including GPUs, NPUs, DSPs, and FPGAs; measure latency, throughput, memory footprint, and power consumption, then drive the changes needed to hit performance targets.
- Design, write, and maintain the C++ application code that hosts inference on device, including pre- and post-processing pipelines, data and memory management, threading, and interfaces to the rest of the embedded system; ensure the combined model and C++ stack meets real-time constraints and fits within device memory budget.
- Build test harnesses to verify on-device accuracy against reference results and catch regressions from optimization or quantization; contribute to tooling for packaging, versioning, and delivering model updates to deployed devices.
- Set best practices for edge deployment, review designs and code, and mentor other engineers on optimization and embedded ML techniques; work closely with research, firmware, and product teams to set realistic performance targets and feed hardware constraints back into model design.

## What You’ll Need

- 10+ years of professional embedded software or systems engineering experience, including at least 2 years focused on deploying ML models to embedded or edge devices; Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, or equivalent practical experience.
- Very strong C++ proficiency; working knowledge of CUDA; hands-on experience with PyTorch and at least one edge inference runtime such as TensorFlow Lite, ONNX Runtime, or TensorRT.
- Practical experience with model optimization techniques including post-training quantization, quantization-aware training, pruning, and distillation; demonstrated ability to profile and optimize for latency, memory, and power on constrained hardware.
- Working knowledge of embedded or edge platforms such as NVIDIA Jetson, Qualcomm, ARM Cortex, or comparable NPUs and SoCs, and of Linux or an RTOS; solid grasp of computer architecture concepts relevant to inference including memory hierarchy, fixed-point arithmetic, and accelerator offload; domain experience in computer vision or sensor processing on device.

You’ll Stand Out

- Hands-on experience deploying computer vision models for detection or tracking tasks on embedded or edge hardware.
- Experience with NVIDIA Jetson specifically, including TensorRT optimization and deployment on Jetson platforms.
- Background in defense, autonomous systems, or robotics where real-time reliability matters.
- Experience building or contributing to model update and OTA delivery pipelines for deployed edge devices.

## What We Offer

- Competitive salary
- ACS Equity Package
- Health, Dental, Vision Insurance
- Paid Time Off

Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. #LI-AS1

## About Allen Control Systems

## Company Overview
- **One-liner**: Allen Control Systems (ACS) is a defense technology company building autonomous robotic weapon stations to counter drone swarms with cost-effective, AI-driven precision.
- **Entity Type**: Private (Series A; recent $200M round at $2.2B valuation)
- **Headquarters**: Austin, Texas, USA (also office in Alexandria, Virginia)
- **Founded**: 2023 (seed round closed April 2024)
- **Founders**: Luke Allen (CTO), Mike Wior (CEO), and Steve Simoni (President) – all U.S. Navy veterans and nuclear engineers

## Core Business
- **Primary industries**: Defense and space manufacturing, counter-unmanned aircraft systems (C-UAS), robotics, AI/computer vision
- **Target customers**: U.S. Department of Defense, allied militaries, national security agencies (B2G)
- **Mission/purpose**: To completely change battlefield economics by lowering the cost per kill of a drone to a few dollars, using existing weapon systems enhanced by proprietary hardware and software.

## Products & Services
- **Bullfrog™ Weapon Stations**: A family of autonomous, remotely operated weapon mounts (variants: M240C, M230, M2, M134, M240) that can be integrated with existing military platforms. Key features:
  - Passive sensing (no radar required) for stealth operations
  - Open architecture for integration with any C2 system
  - AI/ML-based fire control for precise targeting of Group 1–3+ UAS, including swarms and non-jammable drones
  - Effective range up to 1,500m depending on variant
- **Autonomous Fire Control Software**: Machine vision and synthetic data generation engine that continuously updates threat libraries and enables accurate engagement without human intervention.
- **Synthetic Data Training Pipeline**: Generates simulated threat scenarios to keep the system current with evolving drone threats.

## Market Standing
- **Valuation**: $2.2 billion (per 2026 $200M funding round; reported by company and media)
- **Total Funding**: ~$242M (Seed $12M led by Craft Ventures in 2024; Series A $30M led by Craft Ventures in 2025; undisclosed $200M round in 2026)
- **Notable Investors**: Craft Ventures (lead in multiple rounds)
- **Growth Signals**:
  - Headcount grew 262% year-over-year to 131 employees (LinkedIn, 2026)
  - Active job postings increased 392% year-over-year (64 open roles)
  - Recently won a contract for an "Autonomous Identification and Decision" drone solution (FAF contract)
  - Opened Innovation Lab and expanded to a second office (Alexandria, VA)

## Competitive Advantages
- **Passive sensing**: Operates without emitting radar, preserving battlefield stealth.
- **Cost per kill**: Drives engagement costs down to a few dollars per drone.
- **Open architecture**: Integrates with any existing command-and-control system and legacy weapon platforms.
- **Synthetic data generation**: Continuously trains AI models on emerging threats without needing real-world data.
- **Founders’ deep domain expertise**: Navy nuclear engineers with prior startup experience (Luke Allen co-founded Bbot, acquired by DoorDash).

## Strategic Focus
- Scaling production of Bullfrog systems for land and naval platforms.
- Advancing AI/computer vision to defeat larger (Group 3+) UAS and drone swarms.
- Expanding international customer base and partnering with allied defense forces.
- Building a robust supply chain and manufacturing capability in Austin.

## Why Work Here
- **Mission**: Directly contribute to protecting soldiers and changing the economics of drone warfare.
- **Culture**: Described as a remote-friendly organization with a strong engineering focus; HQ in Austin with a satellite office in Alexandria.
- **Work Model**: Remote core, but many roles require on-site presence in Austin for manufacturing and testing.
- **Growth**: Hyper-growth stage – employees have significant ownership and impact.
- **Tech Stack**: State-of-the-art tools: PyTorch, CUDA, Unreal Engine, ROS, Linux, Docker, Git, MLflow, and more.
- **Team**: High density of talent from SpaceX, Firefly, DoorDash, Lockheed Martin, and Carnegie Mellon.
- **Perks**: Not publicly detailed; typical for defense startups include competitive compensation, equity, and a chance to work on cutting-edge hardware-software integration.

## Sources
1. [Allen Control Systems – Company Page](https://www.allencontrolsystems.com/)
2. [Allen Control Systems – About/Team](https://www.allencontrolsystems.com/company)
3. [Allen Control Systems – Careers Page (Greenhouse)](https://job-boards.greenhouse.io/allencontrolsystems)
4. [Allen Control Systems – LinkedIn](https://www.linkedin.com/company/allen-control-systems)
5. [Allen Control Systems – Built In](https://builtin.com/company/allen-control-systems)

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