⚠️Only available to applicants residing in Peru and Argentina⚠️
Our client is a global consulting, software engineering, and digital product development company that empowers the world’s best high-tech companies, disruptive startups, and global enterprises with innovative product design and sophisticated engineering services. Founded in 2008 in Belgrade, Serbia and today has its global headquarters in San Francisco. With consultancy, innovation, and product design offices In Silicon Valley, New York, and London and its technological heart spread across development centers in Central and Southeast Europe, it combines Silicon Valley-based design thinking with the best of engineering talent to support global clients with complete digital product development, from strategy and conceptualization to digital product design and agile engineering on scale. Overall, the company is present in 29 locations in 12 countries, employing more than 2,000 professionals with a vast expertise across a multitude of domains including Healthcare, Retail, Transportation and Smart Mobility, Logistics, FinTech, Green Energy, Media, and Deep Technology.
What you will do:
Our exciting and growing team is looking for a self-starting, ambitious individual who is not afraid to question assumptions. You will have excellent written and oral skills. You will have the ability to effectively work and communicate technical concepts with all levels of an organization including corporate CTOs, CIOs, and Developers. As a member of the knowledge graph team on this role, you’ll be working on dynamic projects that directly support features over multiple products at our Client. You’ll be working with smart engineers in a geo-distributed team. You’ll be crafting and building multi-datacenter distributed systems. Your projects will revolve around crafting systems to evaluate the integrity/quality of an enriched canonical version of the knowledge graph at CLINETS scale. This will involve data heavy lifting with projects focusing on data analytics, data discovery, and algorithms.
What we look for:
Benefits