Job Description
We are expanding our team of motivated technologists with a proven track record of delivering results in technology consulting. We are specifically looking for a Machine Learning Architect with experience in cloud (AWSpreferred) who is passionate about helping customers build AI/ML solutions at scale. Being an experienced technologist with technical depth and breadth, aided with strong interpersonal skills, you will work directly with customers as part of a delivery team, helping to enable innovation by creating state of the artMachine Learning solutions that align to business goals. This role includes responsibilities both as a Professional Services Machine LearningArchitect and as a hands-onMachine Learning engineer on customer engagements. The qualified Machine Learning Architect will have demonstrated the ability to think strategically about businesses, create technical definitions around customer objectives in complex situations, develop solution strategies, motivate & mobilize resources, and deliver results. The ability to connect technology with measurable business value is a critical component to be successful in this role. We seek team members who are self-motivated, driven, collaborative, passionate about machine learning, and want to have a direct positive impact on our customer's business. Strong communication skills and emotional intelligence are also needed to help develop a team that works with you. Work Location: Remote
Rackspace provides hybrid cloud-based services that enable businesses to run their workload in a public or private cloud. Rackspace’s engineers deliver specialized expertise on top of leading technologies developed by OpenStack, Microsoft, VMware, and others through a service known as Fanatical Support. It has more than 300,000 customers worldwide including two-thirds of FORTUNE 100 companies. Rackspace was named a leader in the 2015 Gartner Magic Quadrant for Cloud-Enabled Managed Hosting and has been honored as one of Fortune’s Best Companies to Work For. Rackspace was founded in 1998 and is based in San Antonio, Texas.