Manager, Firmware Engineering
Samsara Remote - USEst. Est. USD 170,000–230,000 / yearSenior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Rust
- C++
- Sql
- Machine Learning
- Tableau
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:
Samsara's AI has helped prevent accidents that would have harmed an estimated 380,000 people per year. Every model we ship runs in the real world, on real roads, protecting real drivers.
Every Samsara dash cam, gateway, and industrial sensor runs AI at the edge. These models detect distracted driving, prevent collisions, and keep workers safe, all in real time on constrained hardware. As Engineering Manager, you'll own how AI moves from a trained model to firmware running reliably on devices in the field across Samsara's customer fleet.
You will drive Samsara’s edge AI strategy while mentoring engineers and delivering high-impact solutions. You will oversee the deployment of next-generation intelligent safety features and video processing by integrating high-performance camera systems and real-time edge computing into Samsara’s fleet and industrial products. In addition, you will establish the technical strategy, cross-functional relationships, and operational cadence required to launch low-latency, high-quality hardware programs at scale.
This is a remote position open to candidates residing in the US. Relocation assistance will not be provided for this role.
Scale: Millions of AI dash cams, 100B+ miles/year (~99% of U.S. roads), 25T+ data points.
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 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:
Lead a team of ~5 firmware and ML engineers. Your team builds, optimizes, and deploys AI models on Samsara's fleet and industrial devices. Your work directly affects whether a driver gets a warning before a collision, not after.
Provide hands-on technical leadership. Lead from the front technically, contributing directly to the design, implementation, and optimization of high-performance production systems.
Set the technical bar for edge ML and embedded systems. You'll guide architecture decisions on latency, power, memory, and model performance, and mentor engineers to
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