Senior Machine Learning Engineer, Edge AI

at  Samsara

WHO WE ARE

Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.
Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, Equipment Monitoring, and Site Visibility. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.

FLEXIBLE WORKING

At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.

ABOUT THE ROLE:

Samsara is looking for an experienced Machine Learning Engineer for our Machine Learning Engineering team. Our Machine Learning team is responsible for leading the teams that build and ship Samsara’s AI features, and the infrastructure that supports them. This includes computer vision, large language models, and multimodal machine learning on edge devices and in the cloud to support our rapidly growing footprint of customers. This organization is building the ML foundation to stay ahead of the needs of our expanding customer base and platform.

IN THIS ROLE, YOU WILL:

• 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

MINIMUM REQUIREMENTS FOR THE ROLE:

• 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.