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Meter (meter.com)

Software Engineer, Models

Posted 8 Days Ago
Hybrid
San Francisco, CA, USA
220K-278K Annually
Entry level
Hybrid
San Francisco, CA, USA
220K-278K Annually
Entry level
The role involves designing and implementing tools for network engineers to produce training data for models, iterating on prototypes, scaling data operations, and monitoring performance metrics.
The summary above was generated by AI

The internet runs the world. But the networks it runs on haven't meaningfully changed in decades. They're brittle, complex, and surprisingly hard to manage at enterprise scale. Meter is building the first truly autonomous networking platform: a physical AI system that learns from real network behavior and resolves issues before they ever surface as problems.

What makes this possible is data. Because we own the entire enterprise networking stack — custom hardware, firmware, orchestration software, and API — we have access to real-world telemetry that no one else can see. But raw telemetry isn't enough. The real signal lives in the minds of expert network engineers: the way they read a dashboard, form a hypothesis, and trace a problem to its root cause.

Our ambition is to embed that judgment into our models at scale and use it to transform one of the largest job categories in tech.

What This Role Is

Nobody is building what we're building, and a big reason for that is data. If we can systematically capture how great network engineers think and encode it into our models, we build something genuinely unreplicable.

That's what this role is about. You'll own the systems and tooling that turn Network Engineer expertise into high-quality training data for our foundation models. This is a 0-1 role: you'll spend real time alongside Network Engineers learning how they think before you write a line of code, then build fast, iterate faster, and scale what works.

You'll know you've succeeded when the Network Engineering team can generate training data independently, at volume, and model performance moves as a result.

What You'll Do Day-to-Day
Build and Own Labeling Tooling
  • Design, implement, and iterate on the tools that network engineers use to annotate issues, log diagnostic reasoning, and curate data for model training and evaluation

  • Build interfaces that feel natural to domain experts: low friction, high signal, and easy to use without engineering support

  • Partner closely with network engineers to continuously learn what's working and what isn't, and update the tooling accordingly

Move Fast and Iterate
  • Ship working prototypes quickly, treat v1 as a learning artifact, and bring proven approaches to production

  • Own the full cycle: design, build, deploy, observe, revise

  • Be comfortable with ambiguity. You're defining the playbook, not following one

Scale the Data Operation
  • Set up metrics and feedback loops that measure tooling effectiveness and its downstream impact on model quality

  • Monitor and troubleshoot data pipelines and tooling in production

  • Help define best practices for labeling workflows and data governance

Who You Are
You're likely a great fit if you
  • Move fast and know when "good enough to learn from" beats "perfect" — and when it doesn't

  • Can prototype quickly and have the skill and fortitude to bring it to production when the time is right

  • Build for the end user: you care whether the people using your tools actually enjoy using them

  • Are curious about domains outside engineering — you'll need to learn how network engineers think, not just what they do

  • Communicate clearly with both engineers and domain experts

  • Thrive with high autonomy and are energized by defining the work, not just executing it

Tech Stack
  • Frontend: TypeScript, React, Vercel

  • Backend: GraphQL, Go, AWS/Azure

Bonus experience:
  • Experience with data labeling, active learning, or annotation frameworks

  • Understanding of real‑time telemetry and large‑scale time‑series data

  • Background building internal tools or developer-facing products

Why Meter, Why Now

Ambitious companies and enduring institutions — Bridgewater, Lyft, Reddit — rely on Meter to keep their employees and locations online and productive. We had to build everything from the ground up to get here: our own enterprise hardware, intuitive software, and streamlined operations.

The models team is where the next chapter gets written. We have the stack, the data, and the customer base. What we're building now is the intelligence layer that makes enterprise networking autonomous. This is the kind of problem that comes around once — and we're at the beginning of it.

Compensation
  • The estimated base salary for this role is between $220,000-$278,000.

  • Additionally, this role is eligible to participate in Meter's equity plan.

By applying to this job you acknowledge that you've read and understood Meter's Job Applicant Privacy Notice.

Top Skills

AWS
Azure
Go
GraphQL
React
Typescript
Vercel
HQ

Meter (meter.com) San Francisco, California, USA Office

San Francisco, CA, United States

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