About Safari AI
Safari AI's vision is to Automate Action of the leading companies in the physical economy, from Entertainment, Live Venues, QSR's, Retail and beyond. The company uses computer vision AI to Measure, Alert and provide AI-generated Recommendations at the operations of leading enterprises such as Merlin/Legoland, 7-11, Tanger Outlets, Charlotte Hornets, Tennessee Titans, and more.
Leadership & Culture
Safari AI is founded by Ali Vahabzadeh, who has a meaningful exit under his belt and has managed large, high-performing Go To Market and Engineering teams. The company is headquartered in Miami with the Engineering team co-located in Vancouver.
About You And How You Succeed At Safari AI
You're excited to build a product and invent a market that hasn't existed before. You read documentation first and are not afraid to ask for help when uncertain. You're looking to take ownership/run a singular project and take advantage of the freedom and culture an early stage startup can provide. You are looking to see through the fluff of the modern AI landscape and explore new ways of achieving measurable ROI. Enjoy a small team size ~10, project team of 1-3.
About the Role
We're hiring an AI Deployment Engineer/Manager to bring Safari AI's computer vision system to life at theme parks, stadiums, retail stores and live venues. You'll report to the Deployment lead and work alongside our ML and Engineering teams. This is forward-deployed work: cameras, edge computers, networks and servers, from the first site survey to a live, monitored system.
You'll get real ownership quickly. In your first 90 days you'll run parts of deployments with support from the team. By month six you'll own smaller deployments and pilot kits yourself. After about 12 months, a successful hire can grow into a senior Deployment Engineer, Solutions Engineering or Client Success role.
This role is remote within the U.S., with regular travel to customer sites.
What You Will Be Doing
- Hardware Provisioning & Linux Administration: Set up and configure edge computers (x86 GPU servers and NVIDIA Jetson), cameras, network switches and 5G/LTE modems before they ship. Maintain, patch and troubleshoot Linux systems in the field, and improve our install scripts and Ansible playbooks.
- On-Site Deployment & Implementation: Travel to customer sites to install and connect cameras and edge devices, verify camera streams and angles, and bring systems online. Work with installation contractors and customer IT teams to keep rollouts on schedule.
- Run pre-deployment assessments covering camera inventory, network layout, bandwidth sizing, redundancy and rack space. Help spec ML/GPU hardware and design site-to-site and VPN connections.
