[Hiring] Senior Embedded Systems Engineer @Loadsmart

Role Description

We are looking for an Embedded Systems Engineer to join our SmartGate team. SmartGate 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.

Qualifications

• 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 between on-camera and edge-device workloads
• Video Streaming & Encoding: experience with real-time video transport protocols such as RTSP and SRT, including configuring and troubleshooting. Able to diagnose streaming issues and instability across edge and cloud systems.
• Video and Image Encoding Fundamentals: Understanding of modern video codecs such as H.265/HEVC and their trade-offs in compression efficiency, bandwidth usage, latency, and compute requirements.
• Remote Troubleshooting and Fleet Management: track record of diagnosing and resolving hardware and software failures without physical device access; experience with Ansible or comparable tools for managing remote device fleets
• Communication: ability to document technical findings clearly and coordinate with contractors, engineering teammates, and customer contacts.

Requirements

• Familiarity with edge AI inference pipelines such as NVIDIA DeepStream, Savant, TensorRT; model training is not required
• Experience with AXIS camera systems and the AXIS Camera Application Platform (ACAP)
• Experience with Docker in embedded or edge computing environments
• Background in logistics, warehousing, or industrial technology is a plus
• Experience authoring operational documentation, kit validation procedures, or runbooks in an environment where processes are being built from scratch.

Benefits

• Competitive base salaries - we believe in rewarding top talent
• Extremely competitive Equity package - become a shareholder in our company!
• Loadie Time Off - PTO and sick days without a limit
• Comprehensive Medical, Dental, and Vision insurance plans
• 401k Match