Senior Manager, Safety AI

About the role:

The Safety AI team builds end-to-end computer vision and machine learning for Samsara’s AI dash cameras – delivering real-time driver safety insights and in-cab alerts. 

As a Sr. Manager of Machine Learning, you will lead teams that fuse on-device computer vision with IMU, GPS, and vehicle diagnostic data to detect, interpret, and surface actionable safety events and continuous risk signals. 

You’ll own the model lifecycle across edge and cloud – data curation, training, evaluation (including shadow/online experiments), deployment, monitoring, and iteration—and develop the core AI platform that powers these capabilities at fleet scale. You’ll partner closely with firmware, full-stack, and Platform teams to ship reliable, low-latency features, grounding detections in the “rules of the road” (e.g., stop signs and speed limits) to maximize precision and customer impact.

Your success will be measured by real outcomes: safety events caught, accident rates reduced, model reliability at production scale, and the velocity at which your team can move from research idea to deployed feature on real vehicles driven by real people.

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 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:

Drive the Safety AI Platform Architecture

• Own the technical direction for Samsara's on-device and cloud safety AI systems — making architectural decisions about what runs on constrained edge hardware vs. cloud, how models are packaged and deployed across more than 2M dashcams, and how the data flywheel is built to drive continuous improvement.
• Lead the transition from individual model deployments to a coherent, system-level platform — one that fuses camera, IMU, GPS, and vehicle telemetry data to detect, interpret, and surface safety events with high precision and low latency.
• Evaluate and integrate emerging AI capabilities (e.g. VLMs, foundation models, multi-task architectures) and determine when they are ready to move from research to production at fleet scale.

Ship Safety AI Features with Measurable Customer Impact

• Partner with product and full-stack teams to define, scope, and ship safety features that reduce accident rates, improve driver coaching outcomes, and deliver quantifiable value to fleet operators.
• Lead experiment design, offline/online evaluation, and go/no-go decisions for new ML-powered features — grounding every launch in real safety metrics, not just model performance benchmarks.
• Own the full model lifecycle: data curation, training, evaluation (shadow and online experiments), deployment, monitoring, and iteration on a continuous improvement loop.

Build and Lead a High-Performing Team

• Lead and grow a team of applied scientists and engineers across CV, sensor fusion, edge ML,  maintaining a culture of high technical standards and strong delivery.
• Hire, coach, and develop senior ICs and early-career talent; create growth paths across both technical and leadership tracks.
• Operate as a tech lead manager: setting the architectural direction while staying hands-on enough to review modeling approaches, unblock technical decisions, and maintain credibility with your most senior engineers.
• 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 offices.

Minimum requirements for the role:

• 8+ years of experience in applied ML or computer vision, with a strong track record of shipping models to production in real-world systems.
• 5+ years leading technical teams of scientists and engineers, including senior ICs — with demonstrated ability to set technical direction, not just manage delivery.
• Experience shipping CV and/or sensor fusion systems that fuse multiple data streams (e.g. camera, IMU, GPS, telemetry) in production environments.
• Demonstrated ability to navigate science-engineering tension: you know when to hold the platform line and when to adapt for research velocity, and you can communicate trade-offs clearly to both sides.
• Experience building and deploying large-scale machine learning systems with feedback loops for continuous improvement.

An ideal candidate also has:

• Customer orientation and intensive focus on improving the customer experience.
• Experience building, deploying, and optimizing AI systems than span edge devices and the cloud.
• Experience with VLMs, foundation models, or multi-task architectures in production settings — particularly in constrained compute environments.
• Background in AV, robotics, or fleet telematics domains where safety and reliability are first-class requirements.
• Contributions to or deep familiarity with the academic research literature in CV and perception and the ability to evaluate what's worth bringing in from research and what isn't.
• MS or PhD in Computer Science, Electrical Engineering, or a related technical field.