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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Aurelius Systems - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Computer Vision, Batch Processing, C++ (Programming Language), Software Debugging, Python (Programming Language), Machine Learning, Performance Tuning, Sensor Fusion, ONNX (Open Neural Network Exchange) Format, TensorRT - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/sr-ml-engineer-perception-aurelius-systems-8292683 ## About the Role * 5+ years building and shipping perception systems on real hardware * Strong Python and C++ with deep ML engineering experience * Computer vision, tracking, and detection in real-time, real-world conditions * On-device deployment experience using TensorRT, ONNX, or equivalent * Track record optimizing perception for embedded compute and latency budgets Where you probably come from: Perception roles at defense companies, autonomy, perception-heavy robotics, or aerospace programs that put perception in front of real targets. We want to talk if: You've shipped a perception system that ran on real hardware against real targets. You know the gap between paper SOTA and what survives field conditions. Not a fit if: Your background is research only without deployment, you're a new grad (we'll have a junior role later), or your CV experience is offline batch processing only. Nice to Haves: * Counter-UAS or aerial target tracking experience * Radar or RF perception * Classified program experience * Sensor fusion in adversarial or denied environments Education: * BS, MS, or PhD in CS, EE, Robotics, or equivalent. Track record matters more than degree. How You Operate: * Extreme bias for action. You ship working perception on real hardware, not slideware * You debug from first principles, not intuition alone * Comfortable with ambiguity and fast iteration in a startup environment * Clear communicator across software, hardware, and operator-facing surfaces * Self directed. You identify what needs to happen next and do it without being told ## Description * ML model development, training pipelines, and on-device deployment * Multi-sensor fusion across EO/IR and other sensors as relevant to the targeting chain * Real-time performance optimization on embedded targets * Mentorship of perception engineers as the team grows * Direct partnership with controls, robotics SWE, and hardware on what's actually achievable, * Build more in 1 month than most engineers build in 1 year. We field test weekly. Your work goes downrange, not into a filing cabinet. * Career velocity is real. At ~10 engineers, there are no layers between you and impact. * Work on a problem that actually matters. Small cheap drones are changing warfare. Our laser systems are the asymmetric answer - infinite magazine, near zero cost per shot, scalable to every base, border, facility, and truck. * Join the densest defense startup ecosystem in the country. California is where the next generation of defense companies are being built. How We Work: Core hours are Monday through Friday, 9 to 6. When we're sprinting toward a demo or field test, the team ramps up - nights, weekends, whatever it takes to ship. When the sprint lands, we ramp down. We don't manufacture intensity for show. ## Related Videos - [Robots 2.0: When artificial intelligence meets steel](https://www.wearedevelopers.com/videos/1452-robots-2-0-when-artificial-intelligence-meets-steel) - [Robots are coming into the wild! Full-Stack Robotics Engineers, be ready!](https://www.wearedevelopers.com/videos/479-robots-are-coming-into-the-wild-full-stack-robotics-engineers-be-ready) - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Focoos AI: Building the Future of Computer Vision](https://www.wearedevelopers.com/videos/1659-focoos-ai-building-the-future-of-computer-vision) - [Intelligent Data Selection for Continual Learning of AI Functions](https://www.wearedevelopers.com/videos/367-intelligent-data-selection-for-continual-learning-of-ai-functions) - [Data: The Deciding Factor in AI Success](https://www.wearedevelopers.com/videos/100310-data-the-deciding-factor-in-ai-success) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)