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Location: Onsite — Austin, TX
Employment Type: Direct Hire, Full‑Time
Job Title: Perception Engineer
About 9 Mothers
The modern battlefield has changed. Cheap, autonomous suicide drones have turned the tactical advantage upside down, and the world is looking for a solution. At 9 Mothers, we aren’t just "innovating"—we are building the shield.
Backed by top-tier investors, we develop AI powered machines designed to intercept and neutralize Group 1/sUAS threats in real-time. Our flagship product is a low-power, counter-drone system built for the edge—on vehicles, at bases, or in a soldier's pack.
Why 9 Mothers?
While others build for "awareness" or "long-term research," we build for the immediate survival of those in harm’s way. We are a team of hackers, engineers, and mission-driven builders who value field-ready capability over polished slide decks. If you want to see your code or hardware in the field next month—not next year—this is your playground.
Position Summary
9 Mothers is seeking a Perception Engineer to own the computer vision and machine learning stack that powers target detection, classification, and tracking in our counter-sUAS systems. The Perception Lead is responsible for the research, development, and deployment of the perception pipeline that enables EDDA to engage aerial threats in real time. This is a senior individual contributor position.
Essential Duties
Own the visual perception pipeline end-to-end, including detection, classification, and tracking of sUAS targets in real time.
Design and train machine learning models that meet latency and accuracy requirements for edge deployment on Jetson-class hardware.
Architect and maintain the dataset and simulation pipeline, including data collection, labeling, curation, augmentation, synthetic data generation, and closed-loop retraining based on field performance.
Optimize inference performance on Jetson platforms, including model pruning, quantization, TensorRT integration, and custom kernel development as required.
Establish the model evaluation framework and metrics used to assess perception performance under operational conditions.
Deliver target state information (position, velocity, identity, uncertainty) to the controls subsystem.
Collaborate with the hardware team on camera, optics, and sensor selection.
Requirements
6+ years of professional experience in computer vision or machine learning, including production deployment on edge hardware.
Demonstrated experience shipping a detection or tracking system under real-world latency, small-object, or adversarial constraints.
Strong engineering skills beyond modeling, including experience with PyTorch or JAX through to deployed, optimized inference.
Proficiency in Python for model development and C++ or Rust for deployed inference.
U.S. citizenship and ability to pass a background check.
Nice-to-Have
Experience working with infrared (IR), thermal, or multi-spectrum camera systems.
TensorRT and NVIDIA Jetson deployment experience at production scale.
Multi-object tracking under challenging conditions.
Multi-modal sensor fusion experience (EO/IR, radar, acoustic).
Synthetic data generation and sim-to-real methodologies.
Prior experience in defense or other safety-critical computer vision applications.
Active security clearance, or eligibility to obtain one.
A passion for building robots or engineering projects as a hobby.
Benefits
Meaningful Early Equity: You aren't just an employee; you are a foundational owner. Your contributions directly drive the value of your stake in the company.
Direct Roadmap Influence: Forget the bureaucracy of big defense. You will have a seat at the table, directly shaping our product and technology trajectory from day one.
Mission-Critical Work: We don't build for "what if." We build systems the Department of War actively needs to counter immediate, real-world threats.
The Builder's Playground: Work in a brand-new lab fully optimized for rapid prototyping, equipped with NVIDIA Jetsons, high-end scopes, and 3-D printers.
100% Employer-Paid Premiums: We cover 100% of your medical, dental, and vision insurance premiums and cover 50% of healthcare premiums for your dependents.
Unlimited PTO: We value results, not clock-watching. Take the time you need to stay sharp and recharge.
Zero Red Tape: You have the autonomy to make technical decisions that would take months of committee approval at a larger firm.
Austin-Based Culture: Join an onsite team in Austin, TX, where we prioritize high-bandwidth collaboration and rapid field-testing.
Relocation Assistance: We want the best talent in the room. If you aren't in Austin yet, we’ll help you get here, to make your transition to the Silicon Hills seamless.
About the Interview
Initial Screening with recruiter - 30 min phone call
1st Round Virtual Interview - peer engineer + SWE Director (45 min via MS Teams)
2nd Round Onsite Interview - CTO + Director + VP + peer(s) (~ 6 hours in-person) **will fly out candidates that are not local
Reference checks & offer
9 Mothers Policy on the Use of Artificial Intelligence (AI) During the Interview Process
The interviewing process is a mutual opportunity for us to get to know each other better. Our goal is to understand your unique background, evaluate your problem-solving abilities, and ensure a strong mutual fit.
AI is a core part of how we work at 9 Mothers—we actively encourage and frequently leverage AI tools in our day-to-day operations. However, during the hiring process, we need to evaluate your fundamental skills and expertise, not the outputs of an AI model.
To ensure a fair and transparent process, we ask that you adhere to the following interview guidelines:
1st-Round Interviews (No AI Allowed): The use of AI tools, assistants, code generation tools, or real-time copilots is strictly prohibited during all first-round interviews and assessments. The use of AI during this stage will result in immediate disqualification from the hiring process.
2nd-Round Interviews (Guided AI Usage): The second-round process includes opportunities to utilize AI. Your interview team will provide explicit guidance on how, when, and which AI tools to leverage during this stage.
We appreciate your cooperation in helping us maintain an authentic and fair interview experience for everyone.