Backend Engineer, Models

San Francisco, CA | Full-Time | Onsite

Meter is building the next generation of networking infrastructure. We design and build the hardware, software, and systems that power enterprise networks, delivering connectivity as a utility rather than a collection of products that customers must integrate and manage themselves.

By owning the entire stack, from switches and wireless access points to firmware, cloud software, and network operations, we have a unique opportunity to fundamentally change how networks are built and operated.

Our ambition extends beyond simplifying networking. We're building autonomous systems that can understand, diagnose, and eventually operate real-world infrastructure. This requires a new class of AI models trained on the complexity of physical networks, supported by the infrastructure to continuously learn from production environments.

We're looking for a Backend Engineer to help build the foundational infrastructure powering Meter's AI Models team.

Our team is developing models that can reason about real-world networks, identify anomalies, diagnose failures, and take action through software. Making this possible requires more than model development. It requires robust systems that can transform massive volumes of real-world network data into reliable inputs for training, evaluation, and inference.

You'll build the backend systems and data infrastructure that connect Meter's physical networks to our AI models. This includes designing scalable data pipelines, building APIs and services, developing tools for model experimentation, and creating the infrastructure that allows research to become production intelligence.

This is a foundational engineering role with significant ownership and direct access to Meter's founders.. You'll work closely with model engineers, researchers, and engineers across Meter's hardware and software stack to build systems that don't yet exist.

• Build foundational data infrastructure: Design and develop scalable systems for ingesting, processing, storing, and accessing massive volumes of network telemetry, configurations, events, and other operational data. Work across distributed systems, streaming data pipelines, and time-series databases to make complex network data accessible and actionable.

• Engineer for production scale: Architect and operate reliable, high-performance backend systems and cloud infrastructure capable of supporting large-scale data processing, model development, and real-time inference as Meter's network footprint expands.

• Develop backend services and APIs: Build the interfaces that connect production network data with model training, evaluation, experimentation, and inference workflows.

• Enable model development: Create reliable data pipelines, datasets, and tooling that allow model engineers to iterate quickly, run experiments, and evaluate model performance against real-world network behavior.

• Connect research to real-world systems: Partner with model engineers and software teams to integrate AI capabilities into production infrastructure, enabling models to reason about and eventually act on live networks.

• Own problems end to end: Drive technical decisions from architecture and implementation through deployment, monitoring, and continuous improvement.

Experience building infrastructure for ML training, evaluation, inference, or experimentation is valuable, but not required. Deep networking expertise is also not a prerequisite.

• Engineers who have demonstrated exceptional ability through the systems they've built, the problems they've solved, and the ownership they've taken.

• People who are intellectually curious, technically ambitious, and motivated by the opportunity to build something that hasn't been done before. They move comfortably between architecture and implementation, challenge assumptions, and care deeply about the quality and impact of their work.

• Engineers willing to work beyond the boundaries of a traditional job description, learn unfamiliar technologies, and collaborate across disciplines to solve difficult problems.

At Meter, you'll have the autonomy to make meaningful technical decisions, work directly with exceptional engineers, and see your work translate into real-world infrastructure operating at scale.

AI is beginning to transform software, but its application to physical infrastructure is still in its earliest stages.

Meter is uniquely positioned to bring intelligence into the physical world. Because we design, deploy, and operate our own networking stack, we have access to the data, operational feedback, and control systems needed to build AI that doesn't just generate answers, but understands and acts on real environments.

You'll join a small team working on foundational technology at the intersection of distributed systems, AI, and physical infrastructure. The systems you build will directly influence how our models learn, how quickly we can experiment, and how intelligence is deployed across networks serving real customers.

We're building toward a future where networks can increasingly operate themselves. This is an opportunity to help build the infrastructure that makes that possible.

• Location: San Francisco, CA. This is a hybrid role requiring three days per week at Meter's corporate headquarters in the Mission District.

• Employment: Full-time.

• Compensation: The base salary range for this role is $160,000–$280,000 annually, depending on experience and qualifications. In addition to base salary, Meter offers meaningful equity ownership and comprehensive benefits.

• Benefits: Comprehensive health coverage, flexible time off, and additional benefits designed to support our team.