Senior Embedded Systems Engineer

ARE YOU INTERESTED IN JOINING AN INNOVATIVE LOGISTICS TECHNOLOGY COMPANY?

Loadsmart is a growth-stage technology company valued at over $1 billion (a true Tech Unicorn)!

We are a collection of industry veterans and user-centered engineers using innovative technology to fearlessly reinvent the future of freight by helping shippers, brokers, warehouses and carriers to move more with less.

With headquarters in Chicago and a globally distributed remote team, Loadsmart continues to attract top talent committed to driving meaningful change. We seek professionals who embody our core values: curiosity, clarity, results, commitment, and teamwork.

We are looking for an Embedded Systems Engineer to join our Smart Gate team. Smart Gate is Loadsmart's Physical AI platform for warehouses and distribution centers — computer vision systems deployed at customer gates that automatically identify trucks, capture license plates and DOT numbers, automate check‑ins, and feed real‑time data into Opendock, our dock and yard management platform. The technology runs on NVIDIA Jetson edge compute devices paired with AXIS IP cameras, packaged in self‑contained outdoor enclosures with LTE connectivity and power systems designed to operate reliably in all conditions, including solar‑powered installations.

This is a fast‑paced, deadline‑driven role: this engineer owns the full hardware‑software integration layer, including the edge software stack, compatibility validation, fleet reliability, and remote troubleshooting. Physical installation at customer sites is performed by contractors.

DEPARTMENT:
Engineering

LOCATION:
United States (Remote)

• Maintain end‑to‑end system integrity across the Smart Gate hardware‑software stack: AXIS IP cameras, NVIDIA Jetson edge compute devices, Savant video pipeline, LTE modems, routing hardware, outdoor enclosures, and power systems; test new hardware generations, firmware versions, and software releases against the production stack before fleet‑wide rollout
• Build, configure, and validate complete hardware kits ahead of customer deployments; verify power budget compliance for solar‑capable configurations; coordinate with installation contractors on setup expectations and post‑install validation
• Deploy and update Smart Gate software across 30+ edge and cloud gates using the Ansible‑based Fleet Management system; manage hardware inventory and prepare Jetson and camera kits for shipment to new sites
• Remotely diagnose and resolve failures across the deployed fleet, including Savant pipeline lockups, camera connectivity issues, and networking misconfigurations; perform on‑site visits when remote resolution is not achievable
• Develop and maintain commissioning runbooks and validation procedures; collaborate with the Computer Vision team on hardware‑side model validation and root cause analysis for missed or incorrect gate events
• Test and benchmark which Smart Gate pipeline workloads can run directly on AXIS camera hardware versus the Jetson; AXIS cameras include the ARTPEC‑8 chip with an onboard AI inference engine (Larod) and support custom applications via the AXIS Camera Application Platform (ACAP).

• Linux: 2+ years of production experience with embedded or server‑side Linux, including service configuration, log analysis, and process‑level debugging; NVIDIA Jetson experience is a strong plus
• Scripting: 2+ years writing Python and/or Bash for production use, including diagnostic tools and operational automation in Linux or embedded environments
• Networking: working knowledge of IP networking (subnets, VLANs, DNS, routing, firewalls) and cellular/LTE; able to independently isolate and resolve edge‑to‑cloud connectivity failures
• Hardware Integration: production experience integrating edge compute platforms (NVIDIA Jetson or comparable), IP cameras, and supporting hardware into validated, production‑ready systems; working knowledge of DC power constraints and solar‑capable configurations
• IP Camera Systems: experience configuring, testing, and troubleshooting IP cameras in production environments; familiarity with camera‑side compute capabilities and the distinction…