Senior Machine Learning Engineer, Edge AI
SamsaraPosted February 7, 2025
San Francisco, California
Energy Management$135,482 - $227,700
Full Time
Job Description
Samsara is seeking an experienced Machine Learning Engineer to develop and deploy AI models on edge devices, focusing on optimizing machine learning for real-time inference and collaborating with cross-functional teams to enhance performance in embedded systems.
Responsibilities
- •Develop and deploy AI models on edge devices using petabyte-scale data from camera and sensor devices.
- •Optimize ML models for real-time inference on edge devices using quantization, sparsification, pruning, and model distillation techniques.
- •Collaborate with firmware and hardware teams to integrate ML models into resource-constrained environments.
- •Improve edge AI performance by profiling and optimizing latency, memory usage, and energy efficiency across different hardware architectures.
- •Stay updated with the latest research in computer vision, deep learning, and embedded AI, applying relevant advancements to products.
- •Work closely with Product Managers to translate customer requirements into scalable and efficient ML solutions.
- •Debug and troubleshoot edge AI deployments, addressing performance bottlenecks and reliability issues.
- •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
- •Compensation/salary range: 135,482 - 227,700 USD
- •Flexible working model (remote and in-person options)
- •Health benefits
- •Employee-led remote and flexible working
- •Samsara for Good charity fund
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