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Mind Robotics

Industrial AI-powered robotics for manufacturing

Forward Deployed Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeNormal, IL, USANo salary listedIn-person

About the Job

Requirements

  • Hands-on hardware and software troubleshooting experience, ideally with microcomputers, embedded devices, cameras, or similar single-board computers.
  • Comfort with Linux system administration, including installing distributions, package management, systemd services, file permissions, and basic shell navigation.
  • Working knowledge of Bash, and ideally Python, for reading and running simple diagnostic scripts and automating routine tasks.
  • Solid networking fundamentals, including TCP/IP, subnets, DNS, DHCP, basic firewall rules, and tools such as ping, traceroute, tcpdump, and ssh.
  • Strong customer-facing communication skills and the self-direction to operate independently onsite while staying tightly coordinated with a remote HQ team.
  • Software development experience and the ability to read, debug, and write production code, with Python preferred.
  • Experience with Git-based workflows, including branching, pull requests, and code review, and working in an Agile/sprint environment.
  • Experience with software testing and validation, including writing test cases, reproducing bugs, and clearly documenting results.

Responsibilities

  • Provision new hardware by installing and configuring Linux, deploying the software stack, and validating device health before bringing units into production.
  • Run diagnostic scripts, collect and interpret system logs, and execute command-line workflows to identify root causes of device or network issues.
  • Configure and troubleshoot local networking, including IP, DHCP, DNS, VLANs, Wi-Fi, and Ethernet, to ensure reliable device connectivity to the backend.
  • Serve as the customer's primary technical point of contact onsite, coordinating with HQ engineering and support to resolve issues and feed field learnings back into the product.
  • Develop code fixes for issues found in the field, root-cause problems down to the code level, and submit changes through Git and code review.
  • Test and validate software trials on field devices by running test plans, capturing results and regressions, and providing a go/no-go before builds roll out fleet-wide.
  • Participate in software sprints by joining planning, standups, and retrospectives, picking up field-related tickets, and helping prioritize the backlog based on customer impact.
  • Turn field observations into reproducible bug reports with logs, steps, and telemetry, and relay software changes and new workflows back to the onsite team.
  • Build scripts and small tools to automate provisioning, diagnostics, log collection, and routine fleet maintenance.
  • Monitor fleet health using dashboards, metrics, and logs to catch issues early and verify that deployed fixes resolved problems.
  • Support staged software rollouts and rollbacks across device groups.
  • Maintain runbooks, troubleshooting guides, and known-issue documentation.

Desired Qualifications

  • Prior experience in a field service, forward deployed, or solutions engineering role.
  • Familiarity with DevOps and software infrastructure tools such as Docker, Ansible, and Portainer.
  • Familiarity with computer vision systems, IP cameras, or industrial IoT deployments.
  • Experience with Git, basic scripting in Python, or remote device management tools.

About the Company

Mind Robotics

Industrial AI-powered robotics for manufacturing

Mind Robotics builds industrial AI and robotics for manufacturing and other physical-world operations, using production-line data as a data flywheel to improve its robots. Its system combines AI-powered robotic hardware with software that analyzes factory data, deploying automated workflows on industrial sites and continually learning from real production data to boost performance and throughput. It differs from competitors through strong backing from Rivian (ownership stake and a board chair) and its automotive-manufacturing background, plus large funding rounds that support scaling AI-powered automation across industries. The goal is to enable widespread, AI-driven robotic automation at industrial scale across manufacturing and other physical-world operations.

Company size
51-200
Company stage
Late Stage VC
Total funding
$1B
Headquarters
Palo Alto, CA
Founded
2025

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