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Senior+ Applied Scientist

Samsara
CompanySamsara
CategoryUncategorised
LocationRemote - US
RemoteRemote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted21 Jul 2026
Last verified2 Aug 2026
SourceEmployer career page (greenhouse)
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Description
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, and Equipment Monitoring. 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: The Samsara Machine Learning / Computer Vision team builds end-to-end applications to power different product pillars at Samsara. We are looking for a talented applied scientist to generate insights and draw value from rich customer interactions, as well as from the 2T+ data points our sensors and cameras collect on an annual basis. This is a remote position open to candidates residing in the United States. This position requires travel up to 5% of the time. Relocation assistance will not be provided for this role. You should apply if: You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely. You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations. You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go. You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes. You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together. In this role, you will:   Build and improve the accuracy of ML / CV models, including retraining and optimizing models to solve Samsara-specific problems.  This will contribute to our R&D roadmap across our four product categories including: Video-based safety - Key focus. Vehicle telematics. Equipment monitoring. Workforce apps and Site Visibility. Work with petabyte-scale data from Samsara camera and sensor devices to develop new models. Optimize models for inference on the backend and/or on edge devices. Partner with firmware and full-stack teams to deploy model for optimal performance and cost. Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs. Collaborate with product team to translate customer needs to ML / CV solutions. 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
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