Lead Hardware Engineer

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Design, configure, and maintain edge computing solutions utilizing Raspberry Pi CM4/CM5, NVIDIA Jetson, and comparable embedded Linux platforms.

• Take ownership of hardware selection and validation for new deployments, ensuring a balance between compute capacity, thermal limitations, cost, and supply chain reliability.

• Architect and uphold systemd service definitions to guarantee reliable, observable, and auto-recovering edge processes.

• Develop and oversee Docker container orchestration strategies for executing CV inference workloads at the edge while ensuring efficient resource utilization.

• Manage our AWS IoT Core integration, including device provisioning, certificate management, shadow state, telemetry pipelines, and configurations across the fleet.

• Design and sustain AWS Greengrass component deployments to effectively manage edge workloads at scale across distributed device fleets.

• Create robust OTA update and rollback mechanisms that consider unreliable field connectivity.

• Integrate with IP camera ecosystems through RTSP stream ingestion and ONVIF device management and discovery protocols.

• Establish and maintain integrations with POS systems to correlate transaction data with vision events in real time.

• Ensure the reliability of the video pipeline, which includes reconnection logic, frame integrity checks, and latency-aware buffering.

• Optimize model inference for constrained hardware, including quantization, TensorRT optimization on Jetson, ONNX runtime configuration, and CPU/GPU affinity settings.

• Profile and enhance memory, thermal, and power envelopes to support CV workloads on edge hardware while maintaining acceptable duty cycles.

• Assess new edge AI hardware as the landscape evolves and provide informed recommendations for adoption.

• Actively utilize AI coding tools and LLM-assisted workflows to enhance productivity — this is an expectation, not a differentiator.

• Rigorously document architecture, deployment runbooks, and failure modes, ensuring that the team handling a 2am alert is well-prepared for success.

• Collaborate across engineering, product, and installation/support teams; this role encompasses a significant cross-functional scope.

⛳️ Requirements

• Over 5 years of practical experience with embedded Linux systems and deploying edge hardware in production environments.

• Extensive expertise in AWS IoT Core and AWS Greengrass, including device provisioning, fleet management, component deployment pipelines, and OTA updates.

• Strong Python programming capabilities with a background in writing production-quality services and tooling (not limited to scripts).

• Proficient with Linux systemd, including writing unit files, managing dependencies, integrating watchdogs, journald, and ensuring failure recovery.

• Experience with the Yocto Project for creating custom embedded Linux distributions tailored to specific hardware targets and minimal production footprints.

• Solid experience with Docker, including multi-stage builds, resource constraints, container networking, and orchestrating multiple services on resource-limited hardware.

• Hands-on experience with RTSP-based camera integration and the ONVIF protocol for camera discovery and management.

• Experience in integrating with POS or other retail transaction systems at the data or protocol level.

• Practical experience with NVIDIA Jetson devices (Nano, Orin NX, AGX, or equivalents) and executing AI inference workloads on them.

• Hands-on experience with Raspberry Pi Compute Module platforms (CM4 and/or CM5) in the context of production hardware design or deployment.

• Proven ability to design for failure, including reconnection logic, graceful degradation, remote observability, and recovery automation.

🏝️ Benefits

• Health insurance

• Professional development