Senior Audio Machine Learning Engineer

Location: Onsite — Austin, TX

Employment Type: Direct Hire, Full-Time

Job Title: Senior Applied Audio ML 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

We are seeking a Senior Applied Audio ML Engineer to use machine learning to make our systems reliably detect, classify, and track acoustic targets. You will bridge the gap between traditional DSP and modern ML, ensuring our interceptors can identify threats under extreme domain shift and outdoor noise.

Essential Duties

• Build Hybrid Approaches: Develop models that combine beamformed channels and multichannel features for robust detection and classification.
• Own the Data Loop: Define labeling strategies, build training/eval pipelines, and implement hard-negative mining to handle diverse outdoor conditions.

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• Ensure Robustness: Directly reduce false alarms caused by wind, rain, and reflections across different terrains and sensor units.
• Ship Edge Inference: Deploy models to edge runtimes with strict latency constraints, integrating diagnostics so the system is operable in real time.
• Cross-Functional Collaboration: Work closely with Hardware and DSP teams to align data, calibration, and performance metrics.
  
  

Requirements

• Experience: You have shipped ML for audio (or similar noisy sensors) into real usage with measurable operational metrics (precision/recall, false alarms).
• Engineering Rigor: Disciplined approach to ML engineering, including reproducible experiments, deep ablations, and systematic error analysis.
• Foundations: Practical understanding of mic-array fundamentals (SNR, aliasing, sync) enough to debug failures and design robust tests.
• Programming: High proficiency in Python; experience with Rust for runtime integration is a significant plus.
• Compliance: US Citizenship and the ability to pass a background check
  
  

Nice-to-Have

• On-device inference optimization (TensorRT, ONNX, quantization)
• Weak/self-supervised learning and domain adaptation
• Fusion/tracking experience (temporal models, confidence calibration)
• Passion for building robots 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.

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• 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 report to the founders. 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

• Application screen phone call (30 min)
• Virtual interview with co-founder/CTO + Director of Engineering (45 min via MS Teams)
• Paid take-home consulting agreement ($500, ~4-8 hours)
• Review work
• Virtual interview with co-founder/CEO (45 min via MS Teams)
• In-person visit to Austin
• Offer