K
Software Engineer
Accepting applicationsKovari · San Francisco, CA
Full-Time Entry C++Pythonaiaterf
Posted
24 Apr
Category
Test
Experience
Entry
Country
United States
About Kovari Industries
At Kovari, we're rethinking how physical work gets done in the age of robotics. We believe that robots capable of valuable, real-world labor are the new foundation for global prosperity.
We're developing general-purpose robots designed to take on the physical, repetitive work that keeps hotels running, starting with housekeeping and core hospitality workflows. By mastering this tractable domain, we're building the foundation for robots that will support an ever-expanding range of physical work.
Founded in San Francisco, Kovari is obsessed with rapid iteration, engineering rigor, and deploying real machines into real environments. The next decade will compress a century of progress in robotics, and we're looking for people who want to leave their fingerprints on that future.
About This Role
We're looking for a founding software engineer to help build the software infrastructure that makes our robots work. This is a generalist role — you'll touch everything from low-level device communication to high-level system orchestration. You'll own critical plumbing that connects hardware, perception, planning, and learning into a coherent, deployable system.
What You'll Do
Build and maintain the core software stack that runs on our robots — communication layers, state management, data transport, configuration, and deployment tooling.
Write reliable, performant code that interfaces with hardware: motor controllers, sensors, cameras, and custom electronics.
Develop internal tools, libraries, and abstractions that accelerate the rest of the engineering team.
Instrument systems for logging, telemetry, diagnostics, and remote debugging of deployed robots.
Build data pipelines that move sensor data from robots into formats useful for analysis, replay, and model training.
Own infrastructure reliability — handle edge cases, failure recovery, system health monitoring, and graceful degradation.
Work across team boundaries — collaborate with controls, perception, ML, and hardware engineers to unblock integration and close gaps.
Contribute to architecture decisions that shape how our software scales across robots, environments, and capabilities.
What You Bring
Strong software engineering fundamentals — you write clean, testable, well-structured code.
Proficiency in Python and C++ in Linux environments.
Comfort working close to hardware — serial protocols, device drivers, real-time constraints, or embedded systems.
Experience with ROS or similar robotics middleware.
Ability to context-switch across the stack and learn new domains fast.
Bias toward shipping — you'd rather deploy something imperfect and iterate than design in a vacuum.
Bonus Points
Experience with real-time systems, networking, or distributed architectures.
Familiarity with sensor integration (cameras, IMUs, LiDAR, encoders).
Background in CI/CD, containerization, or fleet management for physical systems.
Exposure to ML infrastructure — data pipelines, model serving, or training workflows.
Prior work on robots that actually ran in the real world.
Show more Show less
At Kovari, we're rethinking how physical work gets done in the age of robotics. We believe that robots capable of valuable, real-world labor are the new foundation for global prosperity.
We're developing general-purpose robots designed to take on the physical, repetitive work that keeps hotels running, starting with housekeeping and core hospitality workflows. By mastering this tractable domain, we're building the foundation for robots that will support an ever-expanding range of physical work.
Founded in San Francisco, Kovari is obsessed with rapid iteration, engineering rigor, and deploying real machines into real environments. The next decade will compress a century of progress in robotics, and we're looking for people who want to leave their fingerprints on that future.
About This Role
We're looking for a founding software engineer to help build the software infrastructure that makes our robots work. This is a generalist role — you'll touch everything from low-level device communication to high-level system orchestration. You'll own critical plumbing that connects hardware, perception, planning, and learning into a coherent, deployable system.
What You'll Do
Build and maintain the core software stack that runs on our robots — communication layers, state management, data transport, configuration, and deployment tooling.
Write reliable, performant code that interfaces with hardware: motor controllers, sensors, cameras, and custom electronics.
Develop internal tools, libraries, and abstractions that accelerate the rest of the engineering team.
Instrument systems for logging, telemetry, diagnostics, and remote debugging of deployed robots.
Build data pipelines that move sensor data from robots into formats useful for analysis, replay, and model training.
Own infrastructure reliability — handle edge cases, failure recovery, system health monitoring, and graceful degradation.
Work across team boundaries — collaborate with controls, perception, ML, and hardware engineers to unblock integration and close gaps.
Contribute to architecture decisions that shape how our software scales across robots, environments, and capabilities.
What You Bring
Strong software engineering fundamentals — you write clean, testable, well-structured code.
Proficiency in Python and C++ in Linux environments.
Comfort working close to hardware — serial protocols, device drivers, real-time constraints, or embedded systems.
Experience with ROS or similar robotics middleware.
Ability to context-switch across the stack and learn new domains fast.
Bias toward shipping — you'd rather deploy something imperfect and iterate than design in a vacuum.
Bonus Points
Experience with real-time systems, networking, or distributed architectures.
Familiarity with sensor integration (cameras, IMUs, LiDAR, encoders).
Background in CI/CD, containerization, or fleet management for physical systems.
Exposure to ML infrastructure — data pipelines, model serving, or training workflows.
Prior work on robots that actually ran in the real world.
Show more Show less
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