Network Systems Engineer

Gravis Robotics; Zürich; Vor Ort; CHF 150.000 - 190.000; Vollzeit

Zusammenfassung

Gravis Robotics is seeking a software engineer focused on networking to design and own the network architecture across on-machine, worksite, and backhaul layers. You will ensure fast, reliable data flow from sensors to compute nodes, devices, and cloud links across 5G, satellite, or fixed networks.

The role involves deploying and securing networking across global sites, coordinating with Hardware, Perception, and Platform teams, and leveraging tools like Ansible, Terraform, and container

Qualifikationen

• Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or a related field.
• 5+ years of hands-on experience in Network Engineering, Software Engineering, or similar roles.
• Proven experience owning the network stack in a product end-to-end.
• Experience architecting networks with strict timing and synchronization requirements (e.g. PTP).
• Proven experience dimensioning, configuring and deploying in-product network architectures.
• Proven experience with infrastructure as code (Ansible, Terraform, Nix/NixOS).

Aufgaben

• Own the network architecture across three layers: on-machine, worksite, and site backhaul.
• Support and maintain field deployments with special networking needs and customer integrations.
• Secure all product-related network activity using state-of-the-art security mechanisms.
• Shape Linux-level routing configurations for policy-based routing and multi-WAN reliability.

Kenntnisse

Network engineering

Software engineering

Infra as code

Ausbildung

Bachelor's/Master's degree

Tools

Ansible

Terraform

NixOS

Docker

Podman

Grafana

Prometheus

Jobbeschreibung

Gravis Robotics is a high-growth Series A start-up backed by SoftBank, bringing Physical AI to the construction industry, turning heavy construction machines into autonomous robots. Gravis began as an ETH Zurich spin-out, and our unique combination of learning-based automation and augmented remote control lets one operator safely conduct a fleet of earthmoving machines in a gamified environment. Backed by deep robotics research and now deployed across multiple countries with leading construction and equipment partners, our team is rapidly growing to bring this technology to a trillion-dollar industry.

About The 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. While the system is capable of operating in an isolated environment for many applications local or remote connectivity is crucial. As a software engineer with focus on networking, you will be driving the requirements gathering, component evaluation and testing, development, rollout and monitoring of the networking infrastructure that connects our robots. The networks you build span all dimensions: from the network that connects the sensors to the compute nodes on-robot, via robot-to-robots connections, all the way to global cloud connections via satellite links. You will work at the intersection of our Hardware, Perception and Platform teams to ensure the required data reaches our fleet of 20 to 50 ton robots all across the world fast and reliably!

What you'll do

• Own the network arch across three layers: the on machine network carrying sensor and control data, the worksite network linking machines and site infrastructure over wireless LAN or cellular and the site backhaul providing remote connectivity over 5G, satellite or fixed links.
• Support and maintain field deployments with special networking needs & customer integrations
• Secure all product related network activity by applying state-of-the-art security mechanisms
• Shape linux-level routing configuration for Policy-Based Routing prioritizing traffic and ensuring reliability in multi-WAN environments.

What we're looking for

• Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or a related field
• 5+ years of hands-on experience in Network Engineering, Software Engineering, or similar roles
• Proven experience owning the network stack in a product end-to-end
• Experience architecting networks with strict timing and synchronization requirements for aligning sensor data. (e.g. using PTP)
• Proven experience dimensioning, configuring and deploying in-product network architectures
• Proven experience with infrastructure as code (e.g. ansible, terraform, nix/nixOS)

Bonus Qualifications

• Strong Software Engineering skills and solid experience with related tooling (e.g. clangd, cargo, pyrefly)
• Proven experience with monitoring and observability tooling (e.g. grafana, prometheus)
• Hands-on experience with containerization (Docker, Podman)
• Experience with cloud platforms (AWS, GCP, or Azure)
• Experience working with high bandwidth, low latency robotics data (camera streams, point clouds, timeseries data)
• Experience with Robotics & DevOps related tooling (Foxglove, Prometheus, Grafana)
• Experience with Hardware-in-the-loop testing setups
• Regulatory and spectrum management experience for deployment around the world.

This is an opportunity to join a dynamic, multidisciplinary team and to be part of a company that is reshaping heavy construction.

Gravis is an equal opportunity employer. We are committed to building an inclusive and diverse team, and do not discriminate based on race, colour, ancestry, national origin, religion, sex, sexual orientation, age, gender identity, gender expression, disability, veteran status, or other legally protected characteristics.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.