
Transforming physical operations with IoT technology
Samsara is a leading IoT company headquartered in the Design District of San Francisco, CA, specializing in digitizing physical operations across various industries, including transportation, logistics, and construction. With over 1,000 employees and a successful $805 million IPO, Samsara has raised...
Samsara offers competitive salaries, equity options, generous PTO policies, remote work flexibility, and comprehensive health benefits, including pare...
Samsara fosters a culture focused on innovation and technology, aiming to transform underserved operational sectors with IoT and AI solutions. The com...

Samsara • Remote - US
Samsara is hiring a Senior Machine Learning Engineer to develop and optimize ML models for embedded environments. You'll work with Python, TensorFlow, and AWS to enhance driver safety and engagement. This role requires significant experience in machine learning and data analysis.
You have 5+ years of experience in machine learning engineering, with a strong background in developing and optimizing models for embedded systems. Your expertise in Python and frameworks like TensorFlow and Keras allows you to create efficient solutions that operate under constraints. You understand the intricacies of deploying machine learning models in real-world applications, particularly in the context of IoT and edge computing.
Your experience with cloud platforms, particularly AWS, equips you with the skills to manage data pipelines and model deployment effectively. You are familiar with containerization technologies like Docker, which you use to ensure that your models run smoothly across different environments. You have a solid understanding of data analysis techniques and can derive actionable insights from complex datasets, which is crucial for improving operational efficiency.
You are a collaborative team player who enjoys working closely with cross-functional teams, including product managers and software engineers, to deliver impactful solutions. Your communication skills enable you to articulate technical concepts to non-technical stakeholders, ensuring alignment on project goals and expectations. You are passionate about leveraging technology to enhance safety and efficiency in physical operations.
Experience with real-time data processing and analytics is a plus, as is familiarity with edge AI applications. You may have worked in industries such as transportation, agriculture, or construction, where you understand the challenges and opportunities presented by IoT data.
In this role, you will join Samsara's Safety In-Vehicle Experience team, where you will be responsible for developing machine learning models that enhance driver safety and engagement. You will work on real-time safety alerts and AI-driven insights that directly impact millions of drivers on the road. Your work will involve optimizing models for highly constrained embedded environments, ensuring they perform efficiently under real-world conditions.
You will collaborate with product managers to define the requirements for machine learning features and work closely with software engineers to integrate these models into the existing infrastructure. Your role will also involve conducting experiments to validate model performance and iterating on designs based on feedback and data analysis.
You will have the opportunity to mentor junior engineers and contribute to the overall growth of the team by sharing your knowledge and best practices in machine learning and data science. Your contributions will help shape the future of physical operations, making them safer and more efficient.
Samsara provides a dynamic work environment where you can make a significant impact on the future of physical operations. We offer competitive compensation and benefits, including opportunities for professional development and growth within the company. You will be part of a mission-driven team that values innovation and collaboration, working on cutting-edge technology that transforms industries.
Join us in our commitment to improving safety, efficiency, and sustainability in operations worldwide. We encourage you to apply even if your experience doesn't match every requirement — your unique perspective and skills could be just what we need.
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