Backed by Accel and a16z.
About the role
We are seeking an expert Machine Learning Engineer with deep experience in computer vision, model optimization, and deployment on low-cost embedded systems. The ideal candidate will have a strong background in designing, training, and optimizing deep learning models for real-time applications. This role requires expertise in efficient neural network architectures, quantization, model compression, and hardware acceleration techniques to run ML models on resource-constrained devices.
What they're looking for
- Master’s or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, or a related field
- 5+ years of experience in machine learning, deep learning, and computer vision
- Extensive experience in designing and deploying optimized deep learning models for real-world applications
- Proficiency in TensorFlow, PyTorch, ONNX, TensorRT, and other ML frameworks
- Strong experience with model quantization, pruning, knowledge distillation, and hardware acceleration techniques
- Solid programming skills in Python and C++, with a strong understanding of software optimization
More about this role
Swan delivers the future of defense and industry through scalable autonomous products. Swan is backed by leading defense VCs including a16z's American Dynamism fund.
We are seeking an expert Machine Learning Engineer with deep experience in computer vision, model optimization, and deployment on low-cost embedded systems. The ideal candidate will have a strong background in designing, training, and optimizing deep learning models for real-time applications. This role requires expertise in efficient neural network architectures, quantization, model compression, and hardware acceleration techniques to run ML models on resource-constrained devices.
Design, develop, and optimize computer vision models for real-time applications on embedded systems.
Implement model compression techniques such as quantization, pruning, and knowledge distillation to improve performance on low-power hardware.
Deploy machine learning models on embedded platforms, including ARM, NVIDIA Jetson, Qualcomm, or custom ASICs.
Write clean, efficient, and well-documented code in Python and C++, leveraging ML frameworks like TensorFlow, PyTorch, and ONNX.
Develop and fine-tune SLAM, object detection, tracking, and...
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