Job Description
Axion Ray’s mission is to drive innovation by improving the quality and safety of engineered products with new technologies - airplanes, electric vehicles, medical devices, home appliances, consumer electronics - by creating the world’s best proactive management platform, powered by the latest advances in artificial intelligence. Axion leverages bleeding-edge tech & AI stack to solve real-world problems. With investment from top Enterprise SaaS VCs like Bessemer, and key strategic partners such like Boeing and Raytheon, we are uniquely positioned to solve the hardest problems in manufacturing today.
We’re looking for a Deployment Lead to lead our deployments of Axion’s AI platform at our enterprise customers. You will ensure the success of AI deployments with many stakeholders by enabling executives, managers, and users to see value from the Axion platform. You will also lead bringing the best of Axion’s resources to your deployments, looping in data science/AI, eng, and product at the right times. You will also work directly with customers as the day to day point person from Axion Ray. Your team will be cross-functional with support from senior leaders at Axion as well as technical colleagues.
Axion Ray is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.
Axion Ray is an integrity intelligence platform that automates engineering and quality analytics for manufacturing teams. In real time, it extracts actionable insights from unstructured manufacturing data. Its technology detects engineering issues months in advance, allowing businesses to intervene to avoid losses from recalls. The company collaborates with manufacturers from a variety of industries to identify safety and quality risks gleaned from service networks, dealerships, connected sensors, production, supplier management, and other data sources.