Senior Machine Learning Engineer

I'm currently partnered with a venture-backed defense technology company developing autonomous systems for both defense and industrial applications. Backed by leading investors in the national security and autonomy ecosystem, the team is focused on building scalable robotic platforms capable of operating in complex, real-world environments. About the Role They are seeking an experienced Machine Learning Engineer to develop and deploy state-of-the-art computer vision models on resource-constrained embedded platforms. This is an opportunity to work on real-world autonomy problems where performance, reliability, and efficiency matter just as much as model accuracy. The role sits at the intersection of machine learning, computer vision, robotics, and embedded systems, with a strong emphasis on taking models from research through deployment. Responsibilities Design, develop, and optimize computer vision models for real-time autonomous systems Train, fine-tune, and deploy deep learning models for object detection, tracking, classification, and feature extraction Develop efficient perception systems for deployment on low-power embedded hardware Implement model compression techniques including quantization, pruning, and knowledge distillation Deploy and optimize models across platforms such as NVIDIA Jetson, ARM-based systems, Qualcomm AI accelerators, and other edge devices Benchmark and profile inference performance, identifying opportunities to improve latency, throughput, and power efficiency Work closely with robotics and software engineering teams to integrate machine learning systems into production autonomy stacks Develop tooling and workflows for training, evaluation, validation, and deployment Research and implement emerging techniques to improve perception performance in real-world operating environments Qualifications Master's or PhD in Computer Science, Machine Learning, Electrical Engineering, Robotics, or a related discipline 5+ years of experience in machine learning, deep learning, and computer vision Required Skills Strong experience designing and deploying production-grade ML systems Expertise with PyTorch, TensorFlow, ONNX, TensorRT, and related frameworks Experience deploying models onto embedded or edge hardware platforms Strong understanding of model optimization techniques including quantization, pruning, and compression Strong Python and C++ programming skills Experience working with real-world perception systems and large-scale datasets Strong understanding of performance optimization, profiling, and inference acceleration Preferred Skills Experience with SLAM, visual odometry, localization, or sensor fusion Robotics or autonomous systems experience Experience with ROS/ROS2 Experience with CUDA, OpenCL, TensorRT, or hardware acceleration technologies Background in edge AI or embedded machine learning Experience deploying systems onto UAVs, UGVs, or other robotic platforms Startup or high-growth engineering experience Pay range and compensation package Equity package Performance bonus Health, dental, and vision insurance 401(k), FSA, HSA, and commuter benefits Flexible PTO Opportunity to work on cutting-edge autonomy and AI systems with direct real-world impact Significant ownership and influence within a rapidly growing engineering organization Equal Opportunity Statement We are committed to diversity and inclusivity. #J-18808-Ljbffr