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.
What you will be working on regardless the roles
- Primary contributor of Safari AI cloud infrastructure
- Practice engineering best practices for system design, coding, documentation and communication
- Work closely with engineering team members and operation team to identify new priorities and communicate it well
- Contribute to engineering development process improvements
- Set technical direction for cloud infrastructure stack
What you must have
- 4-6 years software individual contributor experiences
- proficiency in AWS or at least one of the following public cloud: GCP/Azure
- proven record on building a complex service from scratch to production
- experiences in delivering incremental features and maintaining reliabilities of a production service
- good understanding in best practices in software development lifecycle (SDLC) and security compliance
Nice-to-Haves
- proven experiences of building a team and mentoring skills
- streaming processing service experiences
- machine learning engineering experiences
