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Teton is seeking a software engineer for its fleet team. The role focuses on building and maintaining backend services, automation, and observability to deploy, monitor, and update software across many remote devices.
The candidate should be comfortable with edge or embedded environments and have experience delivering reliable distributed systems with clear visibility into device health. This position sits at the intersection of AI-enabled scaling and dependable field deployments.
A software engineer on a fleet team typically builds and maintains the systems that deploy, monitor, and update software across many remote devices. This role likely calls for strength in backend services, automation, and observability, plus comfort with edge or embedded environments. A strong candidate brings experience making distributed systems reliable and giving teams clear visibility into device health.
AI changes fleet work by helping predict device failures, flag anomalies in deployment patterns, and automate routine triage across thousands of endpoints. The human part stays in designing safe rollout strategies, judging risk when a device affects patient care, and deciding what should never be automated. This role sits close to that boundary, keeping the fleet dependable while AI assists with scale.
Working here would build hands on experience with computer vision workloads running on edge devices, including how models are packaged, updated, and monitored in the field. It also offers practice with telemetry and feedback loops that show whether AI detections stay accurate over time. That combination is useful for anyone moving toward MLOps or edge AI infrastructure.
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
Per the company, Teton provides an AI and computer vision platform that monitors patient and resident rooms to detect activity and risk in real time.