Responsibilities
- Train end-to-end models for fault prediction, network state modeling, and autonomous repair.
- Build multimodal models over structured networking data and use function-calling to make network decisions.
- Evaluate model performance on real-world hardware and virtualized environments.
- Ship models into production networks and iterate using real-world operational data.
- Collaborate with firmware and application engineering teams.
Requirements
- Experience building, training, and scaling neural networks from the ground up.
- Systems-oriented thinking beyond benchmark performance.
- Interest in modeling the physical world and collaborating across hardware and software.
- Interest in helping establish the technical direction of a new applied research organization.
Benefits
- Access to thousands of H100 GPUs for model development.
- Direct collaboration with the founders and executive team.
- Ground-floor opportunity to shape the roadmap, modeling approaches, team culture, and long-term vision.
- End-to-end ownership from model development through production deployment in real-world networks.
- Opportunity to work with proprietary networking data and full-stack control over hardware, firmware, operating systems, and operations.
Categories
About Meter
Meter provides internet infrastructure for businesses. Headquartered in San Francisco, we were founded in 2015 to build enterprise-grade networks that are faster, more accessible, and more secure. Our full-stack approach combines hardware, software, and operations so that any company can seamlessly run on a reliable and modern network. We believe the internet is a fundamental utility that businesses should be able to turn on as easily as water and electricity. Our team includes people who have helped scale successful companies and recent graduates who are eager to learn and build. We’re looking for people who are excited to work on interesting problems, enjoy learning from and helping each other, and above all, are kind and ambitious. We’re building for the long term, and we’re just getting started.