Senior Machine Learning Engineer, Edge AI

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Requirements:

• BS or MS in Computer Science, Electrical Engineering, or a related field with a focus on ML or embedded systems.
• 5+ years of experience in embedded machine learning or a similar role.
• 4+ years of experience in deploying machine learning models in embedded systems.
• Proficiency in embedded systems programming, including low-level optimization for inference workloads.
• Strong coding skills in C++, Golang, or Python, with experience optimizing ML models for deployment on edge hardware.
• Hands-on experience with ML frameworks like PyTorch, TensorFlow, ONNX, and optimization techniques for edge AI (e.g., quantization, pruning, sparsification).
• Experience in computer vision and media processing on edge/mobile devices, including real-time object detection, tracking, and scene analysis.
• Proven ability to troubleshoot and debug edge AI systems, including profiling inference performance, reducing latency, and optimizing power efficiency.

Responsibilities:

• Develop and deploy AI models on edge devices by working with petabyte-scale data from Samsara’s camera and sensor devices.
• Optimize ML models for real-time inference on edge devices by implementing quantization, sparsification, pruning, and model distillation techniques.
• Collaborate with firmware and hardware teams to integrate ML models into resource-constrained environments, ensuring efficient execution.
• Improve edge AI performance by profiling and optimizing latency, memory usage, and energy efficiency across different hardware architectures (CPU, GPU, DSP, NPU).
• Stay up to date with the latest research in computer vision, deep learning, and embedded AI, applying relevant advancements to Samsara’s products.
• Work closely with Product Managers to translate customer requirements into scalable and efficient ML solutions for real-time video analytics and sensor processing.
• Debug and troubleshoot edge AI deployments, addressing performance bottlenecks, thermal constraints, and reliability issues in production environments.
• Champion Samsara’s cultural principles, fostering a collaborative and growth-oriented team environment.