Samsara
Enterprise · Industrial IoT
- HQ
- San Francisco, US
- Founded
- 2015
- Size
- 2,300+
- Funding
- Public (IOT)
- Website
- samsara.com
Products
Enterprise · Industrial IoT
Samsara has 33 active AI-related job listings, with a significant focus on agents, which accounts for 64% of these roles. Engineering is the primary function hiring for these positions, predominantly in the United States. The company is actively seeking candidates with experience in agent orchestration, model serving, and LLM observability. Over the last 30 days, Samsara posted 13 new AI roles, representing a 18% increase compared to the previous 30-day period.
Currently tracking 24 active AI roles, down 41% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $102k–$319k (avg $208k).
Samsara currently has 15 active AI-related roles in our index. The most common open titles are: Senior Software Engineer I - Agent Foundations (2), Sr. Support Tools Product Manager (2), Staff ML Engineer - ML Infrastructure (2), Staff Machine Learning Engineer - Edge AI (2), AI / Computer Vision (IC). Most positions are in Engineering and Product.
Samsara's active AI hiring is concentrated in: agents (60%), serving infrastructure (27%), application (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Samsara is hiring AI talent in: United States (14 roles), United Kingdom (1 role).
Job postings at Samsara most frequently mention: Software Engineering, Production ML Systems, System Design, Machine Learning, Python.
| Title | Stage | AI score |
|---|---|---|
| Staff ML Engineer - ML Infrastructure Staff ML Engineer focused on building and operating an end-to-end ML platform for industrial AI applications, covering training, experimentation, inference, and edge deployment. The role involves significant infrastructure ownership, reliability, and technical leadership. | ServeData | 8 |
| Staff Machine Learning Engineer - Edge AI Staff Machine Learning Engineer focused on designing and implementing AI product initiatives on Edge devices, optimizing ML models for edge compute constraints, and working with large-scale sensor, diagnostic, video, and text data for industrial operations customers. | ServePost-train | 8 |
| Staff Machine Learning Engineer - Edge AI Staff Machine Learning Engineer focused on designing and implementing AI products on Edge devices, optimizing ML models for edge compute constraints, and working with large-scale sensor, diagnostic, video, and text data for industrial operations. The role involves both tactical solutions and strategic research, with a strong emphasis on production code delivery and cross-functional collaboration. | ServePost-train | 8 |
| Senior Machine Learning Engineer - Edge AI Senior Machine Learning Engineer focused on Edge AI for in-vehicle camera systems. The role involves designing, optimizing, and deploying computer vision and multimodal ML models on constrained edge platforms, applying techniques like quantization and pruning for real-time inference. Responsibilities include collaborating with research and firmware teams, developing performance frameworks, and improving the edge ML toolchain. Requires 5+ years of experience in edge ML deployment, computer vision/multimodal ML, Python/C++, and performance tuning on constrained hardware. | ServePost-train | 8 |
| Staff ML Engineer - ML Infrastructure Staff ML Engineer focused on building and operating an end-to-end ML platform for industrial AI applications, covering training, experimentation, inference (cloud and edge), and deployment. The role emphasizes platform ownership, scalability, reliability, and enabling product teams to ship ML-powered features. | ServeData | 7 |
| Senior Machine Learning Engineer - Platform Senior Machine Learning Engineer to lead the architectural evolution of safety systems, moving from siloed models to a unified Perception Platform Layer. This role involves building robust infrastructure for real-time ML systems across cloud and edge, focusing on performance, reliability, and rigorous evaluation for safety-critical applications. | ServeEval Gate | 7 |
| Senior Machine Learning Engineer - Platform Senior Machine Learning Engineer to lead the architectural evolution of safety systems, moving from siloed models to a unified Perception Platform Layer. This role involves building robust infrastructure for real-time ML systems across cloud and edge, focusing on performance, reliability, and rigorous evaluation for safety-critical applications. | ServeEval Gate | 7 |