Staff Software Engineer

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: Connected Asset Maintenance (CAM) is one of Samsara’s fastest-growing software bets: a brand-new product area focused on transforming asset and fleet maintenance from reactive, paper-based workflows into AI-driven, predictive maintenance programs . We’re building a modern platform that uses rich IoT and telematics data, intuitive interfaces, and centralized workflows to help customers reduce downtime, extend asset life, and run more efficient operations. We are seeking a Staff Software Engineer to serve as a technical anchor for CAM. In this role, you will lead the design and evolution of our predictive maintenance platform, partnering closely with product, data science/ML, design, and customers to build and scale high-impact capabilities for our customers. You’ll be responsible for shaping the architecture for ML-powered features — from time-series modeling and data pipelines to APIs and customer-facing workflows — and for raising the engineering bar across the team. This role is remote and open to candidates residing in the US. 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: Define and drive the technical strategy for CAM’s predictive maintenance platform , including architecture for data ingestion, feature engineering, model serving, and customer-facing workflows. Lead the design and implementation of new predictive models and data products , working closely with ML/data partners to move from proof-of-concept to robust, monitored, and continuously improving production systems. Own and evolve large-scale, distributed systems that process high-volume time-series and event data from Samsara devices and third-party sources, ensuring reliability, performance, and cost efficiency as we grow. Collaborate across the stack (backend, web, and potentially mobile) to deliver end-to-end features—APIs, data models, business logic, and intuitive UI flows—that bring predictive insights into day-to-day maintenance workflows. Partner with product, design, and customer-facing teams to define the roadmap, translate ambiguous business problems into clear technical projects, and measure the impact of what we ship (e.g., reduced breakdowns, fewer emergency repairs, improved shop throughput). Mentor and multiply other engineers on the team through code reviews, design reviews, technical coaching, and by setting high standards for quality, reliability, and velocity. Minimum requirements for the role: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. 8+ years of experience in software design and development, including building and operating production systems at scale. 3+ years building data-intensive or ML-backed products, such as forecasting systems, anomaly detection, recommendation systems, or other high-complexity predictive models (e.g., in fintech, health, reliability, or similar domains). Strong programming fundamentals and deep proficiency in Python for backend and data/ML-related services. Experience designing and operating distributed systems or large-scale microservices (e.g., event-driven architectures, time-series storage, streaming or batch data pipelines). Demonstrated experience leading cross-team or cross-org projects from inception through rollout, including managing ambiguity, driving alignment, and delivering measurable business impact. Strong communication skills and the ability to translate between technical and non-technical stakeholders, especially when discussing trade-offs around reliability, performance, and model accuracy. Proven ability to "sit with the customer" to deeply understand operational pain points, translating vague real-world maintenance challenges into high-impact technical requirements and intuitive AI-driven products. An ideal candidate also has: Master’s degree in Computer Science + Artificial Intelligence. Expertise with time-series data and forecasting techniques , including feature engineering, evaluation, and productionization for predictive maintenance or similar use cases. Hands-on experience with MLOps practices and tooling (e.g., model deployment, monitoring, versioning, experimentation platforms) in partnership with data/ML teams. Experience with full-stack development using technologies such as Go, TypeScript/JavaScript, React, GraphQL, or similar modern stacks in large-scale SaaS applications. Background working with industrial, fleet, or equipment data (e.g., telematics, fault codes, work orders, inspections) and an interest in learning the maintenance domain in depth. Proven track record of mentoring senior engineers and influencing engineering culture, standards, and best practices beyond a single team.