Senior Machine Learning Engineer, Edge AI

Company: Samsara
Location: San Francisco
Posted on: April 1, 2025

Job Description:

Senior Machine Learning Engineer, Edge AIWho we areSamsara (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.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.This is a remote position open to candidates based in the United States and Canada.You should apply if:

• You want to impact the industries that run our world: Your efforts will result in real-world impact-helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely.
• You are the architect of your own career: If you put in the work, this role won't be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development, countless opportunities to experiment and master your craft in a hyper growth environment.
• You're energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers.
• You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by a high-caliber team that will encourage you to do your best.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.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.An ideal candidate also has:
      • 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.Salary Range:The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience.$135,482 - $227,700 USDDiversity and Inclusion:At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems. We are committed to increasing diversity across our team and ensuring that Samsara is a place where people from all backgrounds can make an impact.Accommodations:Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process.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.Scam Awareness:Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in '@samsara.com' or '@us-greenhouse-mail.io'. For more information regarding fraudulent employment offers, please visit our blog post here.Samsara's MissionImprove the safety, efficiency, and sustainability of the operations that power the global economy.
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Keywords: Samsara, San Francisco , Senior Machine Learning Engineer, Edge AI, Engineering , San Francisco, California