2027 US AI Engineering – New College Graduate
Develop cloud and AI platforms spanning GPU infrastructure, Kubernetes orchestration, model training and inference, AI agents, and distributed systems that power large-scale AI workloads.
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide guaranteed performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
What You’ll Do
Requirements
Preferred Qualifications
Benefits
Develop cloud and AI platforms spanning GPU infrastructure, Kubernetes orchestration, model training and inference, AI agents, and distributed systems that power large-scale AI workloads.
Build and enhance scalable full-stack applications, solve distributed systems challenges, and use AI tools to improve coding, testing, design, and troubleshooting while contributing to product and architecture decisions.
Développez et qualifiez des prototypes et outils de simulation numérique pour les expertises du ministère des Armées, au sein d’une équipe travaillant sur des technologies variées et des calculs scientifiques.
Build and ship user-facing features alongside experienced engineers, gaining hands-on experience across the development cycle while learning how technical decisions connect to real user and business needs.
Develop and test Linux infrastructure and security products, investigate production issues, improve software delivery automation, and contribute to code reviews while building engineering skills with support from experienced engineers.