Senior Machine Learning Engineer - Edge AI

February 15

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Samsara

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Samsara is a technology company that provides a comprehensive operations platform aimed at improving the efficiency, safety, and sustainability of organizations. Their solutions include video-based safety, vehicle telematics, equipment monitoring, workforce applications, and site visibility. Samsara serves a wide range of industries, including transportation, logistics, construction, and government. The platform connects people, systems, and data, enabling organizations to make faster, data-informed decisions. Samsara's Connected Operations technology helps complex organizations operate more effectively by offering real-time GPS, proactive alerts, compliance training, and asset tracking.

1001 - 5000 employees

Founded 2015

🏢 Enterprise

🚗 Transport

🔐 Security

💰 Seed Round on 2014-08

📋 Description

• 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.

🎯 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.

🏖️ Benefits

• Full time employees receive a competitive total compensation package along with employee-led remote and flexible working • health benefits • Samsara for Good charity fund • and much, much more.