Top Tech Jobs & Startup Jobs

Lead and grow a distributed software/firmware engineering team across multiple time zones, prioritize and execute the technical roadmap for AI vision products, manage releases and sprints, define requirements and report progress, foster high-performance culture, and periodically travel to support teams and customers.

Lead multi-site AI inspection deployments from signed contract through stable production. Manage applications engineers and technicians, customer stakeholders, staffing, scheduling, commissioning, acceptance, and handoff. Build repeatable deployment processes, training frameworks, dashboards, and continuous-improvement systems. Translate field issues into product and engineering improvements while tracking deployment performance and driving predictable customer expansion.

Work with founders and regional sales leadership to scale US/Mexico go-to-market by defining GTM strategy, building sales enablement collateral, owning HubSpot CRM architecture and reporting, running cross-functional experiments, supporting hiring and onboarding, and participating in customer and partner engagements.

Develop and maintain responsive full-stack web interfaces and backend Python systems for an edge AI vision product. Build, deploy, test, and iterate on features managing data capture, labeling, training, and operator workflows. Collaborate with AI teams to prototype and ship user-facing features, prioritize UX, and optimize for resource-constrained and hardware-integrated environments.

Build and run Guadalajara operations: set up office and inventory hub, receive and prep shipments, create customs and freight processes, manage brokers/forwarders, maintain Cin7 inventory, coordinate with Finance and Sales, write SOPs, onboard hires, and handle ad-hoc operational tasks.

Own and operate the company-wide automated E2E test platform: build nightly CI/CD pipelines against real hardware (NVIDIA Jetson), manage physical test rigs and HIL infrastructure, eliminate flakiness, validate production signal paths (PLC/EtherNet-IP, digital I/O, HDMI), enable squad-level SDETs with frameworks and device pools, and triage system-level failures spanning hardware, OS, networks, and edge containers.

Lead a team to manage technical deployments in manufacturing, ensuring stable installations and high customer satisfaction. Responsibilities include project management, team leadership, and building operational infrastructures for scaling deployments.

Design, build, and maintain software for edge AI cameras. Requires strong Embedded Linux experience, C++, and Python skills. Prioritize reliability and performance across OS and application stack.

The Applications Engineer installs and integrates AI vision systems on production lines, troubleshoots issues, and provides customer support in manufacturing environments.

The Systems Integration Engineer will lead mechanical integration of AI camera systems in automation machines, ensuring robust designs and optimal field performance while supporting new line deployments and training customer teams.