Networking is one of the most fundamental industries in all of technology. For the first time, Meter has unified the full networking stack; and now we are making it autonomous.
We are building a neural network-driven system for reasoning in raw computer networks to solve any and all networking problems. As described on Meter.ai, we’re building models in a closed-loop system that takes (as input) real-time telemetry, logs, and events on the network to autonomously troubleshoot, improve performance, and resolve issues.
To make this possible, we don’t just need great models; we need infrastructure that gives those models clean, versioned, low-latency access to the right data, across training, evaluation, and deployment.
Why this role mattersEvery Meter network deployed in the field is a rich data source for our Models team. But without careful infrastructure design, this data becomes fragmented, stale, or inconsistent. Your job is to make sure that never happens. You’ll own the core data interface that powers our model development, experimentation, evaluation, and real-time inference.
This is a foundational role with outsized impact. Your work will define how quickly we can train new models, how reliably we can evaluate them, and how seamlessly they can operate in production across hundreds of real-world networks. You’ll partner tightly with modelers to ship systems that feel elegant, scalable, and bulletproof.
What you'll doDesign and implement the Models API: a unified interface for accessing training, evaluation, and deployment data across raw, transformed, and feature-engineered layers
Ensure backwards compatibility and feature versioning across constantly evolving schemas
Build scalable pipelines for ingesting, transforming, and serving petabytes of data across Kafka, Postgres, and Clickhouse
Create CI/CD workflows that evolve the API in lockstep with changes to the underlying data schema
Enable fine-grained querying of historical and real-time data for any network, at any point in time
Help define and enforce the principle of "smart data, dumb functions": doing as much as possible in the data layer to keep downstream code minimal
Collaborate with modelers to co-design training and evaluation pipelines that are reproducible, debuggable, and fast
Own performance across key endpoints to meet real-time serving constraints
Have experience designing large-scale data infrastructure, ideally across batch and streaming modes
Think deeply about schema design, versioning, and data quality
Care about making systems simple to use and hard to misuse
Enjoy partnering closely with research or modeling teams
Thrive in early-stage environments and like building from scratch
Kafka, Postgres, Clickhouse
Python, Go
AWS, Azure
We think about Meter's compensation package as a combination of salary, equity, benefits, and the experience of working with a talented team to make the biggest impact of your career.
The estimated salary range for this role is $160,000 - $230,000 depending on experience, and it is eligible for equity in Meter. We also offer:
Medical, dental & vision coverage for you and your dependents
Annual memberships to One Medical, Headspace, and Wellhub
401k (traditional and Roth options)
Flexible time off
Commuter benefits
Parental leave
Onsite meals (San Francisco office)
Top Skills
What We Do
Our bet with Meter is simple: we’ll all use the internet more than we do today.
That future depends on networking infrastructure—the invisible plumbing powering every application, space, and data center. But today’s infrastructure is dated and inconsistent, so we’re rebuilding it from the ground up.
We design the hardware, write the firmware, build the software, deploy the networks, and run support.
It’s a single, integrated networking solution that scales from offices, warehouses, and large campuses to data centers—and today, it’s powering some of the world’s most ambitious organizations.
Why Work With Us
We’re a group of kind and ambitious people who want to do the best work of their career. The work we do across hardware, software, and operations is hard and long-term oriented. We are colleagues who view fast-paced and changing environments as an opportunity—not a bug—and find the agency to move things forward.
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