San Francisco, CA, US
Since its inception, over ten years ago, Joyent has lived on the leading edge of technical innovation. The Joyent team pioneered public cloud computing (and hybrid cloud), nurtured and grew Node.js into a de facto standard for web, mobile and IoT architectures, and was among the first to embrace and industrialize containers, compute-centric object storage, and what is now coming to be known as serverless computing. Common to everything we do is a deep belief in open source and open source communities. Looking forward, we believe that containerization will transform the way software is developed and deployed and will be driver of innovation in machine learning systems, serverless architectures, and more. If you are excited by the challenge of attacking big, complex, web infrastructure problems and share our passion for containers and open source software, we would love to talk.
We are building a new open machine learning platform, that is cloud agnostic, portable and can manage ML workloads federated across clouds — public, private or hybrid. The platform empowers users to build container and cloud-native AI solutions by enabling leading open source ML frameworks like Tensorflow to run on a multi-cloud Kubernetes engine with the ability to switch between regular (CPU) and accelerated compute resources (GPGPU, FPGA, etc). This platform will cater to thousands of applied researchers, millions of users, and billions of data objects.
In this role you will:
First and foremost, you have a positive attitude & aptitude to learn and execute quickly. You get things done and done well. You have:
Joyent, a wholly-owned subsidiary of Samsung, is the open cloud company. With its Triton Kubernetes services and support, Joyent helps its customers build and operate modern cloud native applications across multiple clouds. Joyent’s Triton Private Regions provide low cost, dedicated cloud infrastructure that gives its customers the ability to own their data and control their cloud costs.
To apply, please submit a brief introduction, a copy of your resume, and a link to your Github or LinkedIn profile to firstname.lastname@example.org with Product Engineer: Machine Learning in the subject. Qualified applicants with criminal histories will be considered for the position in a manner consistent with the Fair Chance Ordinance.
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