
About Samsara
Transforming physical operations with IoT technology
Key Highlights
- Public company following an $805M IPO
- Raised $930M in funding across multiple rounds
- Serves thousands of customers including Penske and Sysco
- Headquartered in San Francisco, CA with 1001+ employees
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...
🎁 Benefits
Samsara offers competitive salaries, equity options, generous PTO policies, remote work flexibility, and comprehensive health benefits, including pare...
🌟 Culture
Samsara fosters a culture focused on innovation and technology, aiming to transform underserved operational sectors with IoT and AI solutions. The com...
Skills & Technologies
Overview
Samsara is seeking a Staff Machine Learning Engineer to build end-to-end AI solutions and core ML infrastructure. You'll work with large-scale data and collaborate with cross-functional teams. This role requires expertise in Python, TensorFlow, and machine learning technologies.
Job Description
Who you are
You have 5+ years of experience in machine learning and data science, with a strong background in building and deploying machine learning models at scale. You are proficient in Python and have hands-on experience with frameworks such as TensorFlow and PyTorch, enabling you to develop robust AI solutions. Your expertise extends to cloud platforms like AWS, where you have deployed machine learning applications and managed data pipelines. You are familiar with containerization technologies such as Docker and orchestration tools like Kubernetes, which you use to streamline deployment processes. You possess strong analytical skills, allowing you to interpret complex datasets and derive actionable insights that drive business decisions. You thrive in collaborative environments, working closely with ML engineers, data scientists, and software engineers to deliver impactful solutions. You are passionate about leveraging AI to solve real-world problems and are eager to contribute to the digital transformation of physical operations.
What you'll do
In this role, you will be responsible for designing and implementing end-to-end machine learning solutions that address critical challenges faced by our customers in physical operations. You will work with petabyte-scale data, including sensor, diagnostic, video, and text data, to develop models that enhance operational efficiency and safety. Collaborating with cross-functional teams, you will contribute to the development of core product features and optimizations, ensuring that our AI solutions are scalable and effective. You will also engage in model training and evaluation, applying best practices in machine learning to improve model performance continuously. Your role will involve mentoring junior engineers and sharing your knowledge of machine learning techniques and tools. You will participate in code reviews and contribute to the overall technical direction of the team, ensuring high-quality deliverables that meet customer needs. Additionally, you will stay updated on the latest advancements in AI and machine learning, integrating new techniques and technologies into our workflows to maintain a competitive edge.
What we offer
At Samsara, we offer a dynamic work environment where innovation is encouraged, and your contributions can make a significant impact. You will have the autonomy to explore new ideas and technologies while working alongside a talented team of professionals. We provide competitive compensation and benefits, including flexible work arrangements to support your work-life balance. Our commitment to professional development means you will have access to resources and opportunities to enhance your skills and advance your career. Join us in shaping the future of physical operations through cutting-edge AI solutions that drive efficiency and sustainability across industries.
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