Senior Machine Learning Engineer - Edge AI

Summary

Join Samsara's Machine Learning Engineering team as an experienced Machine Learning Engineer and develop cutting-edge AI models for edge devices. You will optimize ML models for real-time inference, collaborate with firmware and hardware teams, improve edge AI performance, stay updated on the latest research, and work closely with Product Managers. This remote position, open to US-based candidates, offers the chance to impact global industries by improving safety, efficiency, and sustainability. You'll be part of a high-caliber team in a hyper-growth environment with opportunities for career development. The role involves deploying AI models on edge devices using petabyte-scale data and troubleshooting edge AI deployments.

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
• Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices

Preferred Qualifications

• Ph.D. in Computer Science, Electrical Engineering, or a quantitative discipline (e.g., Applied Math, Physics, Statistics)
• Experience deploying AI models for real-time processing on edge hardware such as NVIDIA Jetson, Qualcomm Snapdragon, ARM Cortex, or Apple Neural Engine
• Expertise in large-scale edge ML deployments, including firmware integration and model lifecycle management
• Experience in DSP optimization for computer vision applications on Qualcomm Hexagon, ARM NEON, or similar architectures
• Knowledge of power and thermal optimization techniques to balance AI performance with device constraints in edge computing environments

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