Posted 2 days ago
Software Engineer - Infrastructure
AI Summary
At Gravis, we build high tech systems that give machine operators super human capabilities. To adapt in real time to changes in the environment the Gravis Rack fuses data from LiDAR, cameras, GNSS, and hydraulics into an autonomous control system.
About this role
At Gravis, we build high tech systems that give machine operators super human capabilities. To adapt in real time to changes in the environment the Gravis Rack fuses data from LiDAR, cameras, GNSS, and hydraulics into an autonomous control system. As our engineering team grows we need world-class infrastructure to support the full development lifecycle of these systems: from developer tooling to continuous integration, testing, and deployment at scale.
As our software engineer with focus on infrastructure, you will be driving the requirements gathering, development, rollout and operation of the related infrastructure. The systems you build and operate power every line of code, commit, and production deployment at Gravis. You will work at the intersection of our Platform, Autonomy, Perception and Interface teams to enable high velocity & quality of developer workflows. At the same time, you ensure the continuous deployment of software to a fleet of 20-ton robots all across the world.
Responsibilities
Design, build and operate end-to-end CI pipelines covering software builds, testing, linting, static analysis, versioning, releases, and deployment ranging from edge devices in the field to cloud infrastructure
Own Configuration Management and infrastructure provisioning across the software department
Collaborate closely with Autonomy and Perception engineers to understand requirements and translate them into reliable, scalable development environments for maximum development efficiency and velocity
Own, operate and enhance in-office Hardware-in-the-loop test setups
Own, operate and enhance fleet monitoring systems
Closely collaborate with ML Ops Engineers and Simulation Engineers on shared infrastructure
Required Qualifications
Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or a related field
3+ years of hands-on experience in Software Engineering, DevOps, data engineering, or similar roles
Strong Software Engineering skills and solid experience with related tooling (e.g. clangd, cargo, pyrefly)
Proven experience building and managing CI pipelines for build, test and ML workloads (e.g. GitHub Actions or GitLab CI)
Proven experience with infrastructure as code (e.g. ansible, terraform)
Proven experience with monitoring and observability tooling (e.g. grafana, prometheus)
Hands-on experience with containerization (Docker).
Experience with cloud platforms (AWS, GCP, or Azure).
Experience with software packaging & versioning (docker images, debian packages).
Bonus Qualifications
Don't meet every requirement? We still want to hear from you. These are nice-to-haves, not dealbreakers:
Experience working with robotics data (point clouds, camera streams, timeseries data).
Experience with Robotics & DevOps related tooling (Foxglove, Prometheus, Grafana)
Experience with Hardware-in-the-loop testing setups