Infrastructure Engineer

Actor; Mountain View (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Actor is seeking an infrastructure engineer to build and run the software stack on deployed hardware, manage the data pipeline, and maintain deployment tools across field sites. You will handle logging, telemetry, remote updates, and health services to keep machines running reliably.

You will own end-to-end data pipelines, enabling log collection from devices with limited connectivity, organizing data, and feeding training jobs for ML models.

Qualifications

• Experience building and operating production infrastructure.
• Proficiency in Python and at least one systems language on Linux.
• Familiarity with containers, CI/CD, object storage, databases, and monitoring.
• Experience handling data for ML workflows or willingness to learn.
• Willingness to travel to jobsites regularly.

Responsibilities

• Build and maintain software on deployed hardware, including logging, telemetry, remote updates, and health services.
• Own the data pipeline end-to-end: collect logs, store, process, and feed training jobs.
• Develop internal deployment management tools to track machine state and health.
• Lead deployments on site: install, configure, validate, and hand off for faster future deployments.
• Set up and maintain cloud and CI infrastructure tying the system together.

Skills

Production infra

Python

Systems programming

Linux

CI/CD

Containers

Object storage

Databases

Monitoring

ML data handling

Tools

SSH

Job description

You'll build and run the infrastructure behind every machine we deploy: the software on the hardware, the pipeline that moves data from the field into model training, and the tools we use to manage all of our deployments.

What you'll do

• Build and maintain the software that runs on our deployed hardware: logging, telemetry, remote updates, and the services that keep the machine's computer healthy without anyone on site.
• Own the data pipeline end to end: getting logs off machines with unreliable connectivity, storing and organizing them, running labeling and processing, and feeding training jobs.
• Build our internal deployment management tools: which machine is running what, where, with which config, and whether it's healthy.
• Lead deployments on site: install, configure, validate, and hand off, and improve the process so the next one is faster.
• Set up and maintain the cloud and CI infrastructure that ties all of this together.

What you need

• Experience building and operating production infrastructure: data pipelines, deployment systems, fleet or device management, or similar.
• Python and at least one systems language, on Linux. Comfortable both on an embedded box over SSH and in a cloud console.
• Experience with the usual infrastructure stack: containers, CI/CD, object storage, databases, and monitoring.
• You've managed data for machine learning before, or are ready to learn how training workflows consume it.
• Willing to travel to jobsites regularly. Experience with field hardware or heavy equipment is a plus.