Deployment Engineer

About the role

The Deployment Engineer at Dyna Robotics owns the full lifecycle of robot fleet operations in customer environments, from initial site survey to post-incident recovery. This role requires driving remote diagnostics and executing hands-on interventions to resolve complex hardware and software failures. You will act as the critical link between our engineering teams and on-site customers, ensuring professional representation at every interaction. Success is measured by your ability to translate ambiguous field data into clear, reproducible evidence that guides fleet-wide fixes. You will own the configuration of network and deployment infrastructure that keeps robots securely connected and operational. The position demands comfort with deep troubleshooting across software, network, and mechanical domains simultaneously. You will coordinate schedules and communicate progress directly with customers to maintain trust and alignment. Finally, you will partner with product and engineering teams to turn incident reports into durable improvements that reduce future on-site burden.

Key facts

What you'll do

Investigate remote service failures using structured diagnostic playbooks and operator reports to drive rapid robot fleet response.

Operate deploy and rollback stations that manage production changes, ensuring clean transitions and providing incident evidence for partner teams.

Represent Dyna Robotics on-site at customer locations, coordinating schedules and maintaining professional conduct in showrooms, conferences, and live operations.

Translate fleet-wide error signals and incident evidence into clear, reproducible reports that enable engineering teams to implement systemic fixes.

Perform hands-on hardware debugging, including swapping arms, reseating connectors, and tracing flaky cables to restore robot functionality.

Configure and maintain Linux-based robot systems, applying strong shell scripting, systemd service management, SSH access, and log analysis techniques.

Design and manage network topologies for robot deployments, handling DHCP/DNS, firewall rules, VPN solutions such as Tailscale/WireGuard, VLANs, and WiFi behavior.

Mitigate hostile network conditions by configuring captive portals, locked-down firewalls, and other security controls without disrupting robot operations.

Ensure GPU and server hardware reliability by managing drivers, monitoring nvidia-smi outputs, observing thermal and power constraints, and running basic benchmarking.

Support inference workloads on proprietary embodied AI foundation models, maintaining the performance and stability required for commercial-grade physical work.

Travel to customer sites on short notice to address urgent issues, minimizing downtime for deployed robot fleets across multiple industries.

Balance field execution with remote troubleshooting, using clear communication to keep stakeholders informed throughout the incident lifecycle.

Continuously improve deployment tooling and operational procedures to reduce manual effort and increase fleet reliability over time.

Requirements

The posting states a bachelor's degree requirement. A degree is required as stated in the official listing.

Strong Linux fundamentals are necessary, including shell scripting, systemd services, SSH, log analysis, and Docker.

Solid networking skills must cover DHCP/DNS, firewalls, VPN solutions such as Tailscale/WireGuard, VLANs, WiFi behavior, and managing hostile networks with captive portals and locked-down firewalls.

Comfort with GPU/server hardware and inference workloads is required, including drivers, nvidia-smi, thermal/power constraints, and basic benchmarking.

Hands-on hardware debugging instinct is mandatory, including physical intervention such as swapping arms, reseating connectors, and tracing flaky cables.

Calm, structured incident response and clear written communication for status updates and post-mortems are required.

Willingness to travel to customer sites on short notice is necessary.

Practical notes

The position is based in Redwood City, California, requiring onsite presence five days per week plus occasional travel.

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds.

Candidates often solve a coding problem, discuss past projects, and answer system design questions.

Some loops include a take-home task.

Final rounds typically cover team fit and give candidates a chance to ask questions.

Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer.

Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

Work in this field centers on general-purpose robots powered by proprietary embodied AI foundation models with industry-leading generalization and real-world performance.

These systems are already deployed across multiple industries to perform commercial-grade physical work.

The team is composed of professionals with backgrounds at Google DeepMind, Meta, and Cruise, supported by investors including CRV and First Round.

The role blends software, networking, and hardware troubleshooting in field and remote environments.

Career growth

Engineering careers usually progress from individual contributor to senior, staff, and principal levels.

Some engineers move into management and lead teams of five to twenty people.

Others stay on the technical track.

Growth follows demonstrated impact, not tenure alone.

A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship.

Moving up usually requires owning outcomes end to end rather than completing assigned tickets.