About this role
About the Role Join Samsara's Safety AI team as the most senior individual contributor, charged with taking research into production in safety-critical perception systems that run on millions of edge devices and in the cloud. You’ll sit at the intersection of cutting-edge computer vision and large-scale production infrastructure, building real-time models that operate on the road. What You'll Do
- Architect end-to-end computer vision pipelines for real-world safety detection — object detection, tracking, semantic segmentation, multi-camera fusion, and beyond
- Drive the technical roadmap for edge and cloud perception, including how we optimize and deploy models on constrained hardware without sacrificing accuracy
- Partner closely with our hardware and firmware teams — we build our own devices, which means you'll have a rare ability to co-design the full stack
- Work with petabyte-scale multimodal data (video, sensor, telematics, diagnostics) to train and iterate on production models
- Stay at the frontier of CV and perception research and translate what matters into shipped product
- Mentor and technically guide senior scientists and engineers across the team
- Bring clarity to ambiguous problems — translating customer and business needs into precise, solvable engineering challenges
- Champion, role model, and embed Samsara’s cultural principles as we scale globally and across new offices What We're Looking For
- Master’s or PhD in Computer Science, Electrical Engineering, Robotics, Computer Vision, or related quantitative field
- 10+ years as a scientist or ML engineer, with experience leading end-to-end AI systems in production
- Deep expertise in computer vision (e.g., object detection, tracking, segmentation) for real-world environments
- Experience with multimodal perception and sensor fusion (e.g., camera, lidar, radar, GPS/IMU)
- Experience with transformer-based architectures and vision-language models (VLMs/VLAs)
- Experience building and deploying real-time or edge ML systems optimized for low-latency inference
- Demonstrated ability to drive systems from research through production deployment, including performance optimization and reliability at scale
- Ideal candidate also has experience applying perception to real-world systems such as driver assistance, fleet safety, or operations automation
- Publications or patents at top-tier venues (CVPR, ICCV, ICRA, NeurIPS) Nice to Have
- Experience applying perception to real-world systems such as driver assistance, fleet safety, or operations automation
- Publications or patents at top-tier venues (CVPR, ICCV, ICRA, NeurIPS) Compensation & Benefits
- Salary range: Not disclosed in posting
- Benefits: Not specified in posting