DigitalOcean
Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here.
We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
We are looking for a Cloud Support Engineer SME with deep expertise in Kubernetes, AI/ML workloads, and GPU infrastructure who is passionate about helping our customers scale and innovate with cutting-edge technologies.
As a Cloud Support Engineer at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. You will be a key member of our advanced support team, helping DigitalOcean's strategic customers succeed by providing white-glove support and guidance across complex technical domains.
Responsibilities
Act as a technical subject matter expert (SME) for Kubernetes, AI/ML workloads, and GPU-backed infrastructure. Troubleshoot and resolve advanced support cases related to orchestration, performance tuning, container networking, and GPU-based compute. Engage directly with our strategic and high-value customers via tickets, Slack, email, and live sessions. Partner with Engineering and Product teams to provide feedback on platform usability, bugs, and customer needs. Help shape internal runbooks, SOPs, and documentation to scale AI/ML and GPU-related support. Participate in incident management, root cause analysis, and retrospective reviews. Contribute to the architecture and optimization of customer workloads for high availability and cost efficiency. Educate and mentor internal team members on Kubernetes and GPU-based architectures. Influence roadmap priorities by surfacing recurring pain points and opportunities. Requirements
5+ years in technical support, DevOps, solutions engineering, or SRE roles. Deep experience with Kubernetes (preferably CKA-certified) in production environments. Experience supporting AI/ML workflows using GPUs (e.g., NVIDIA A100, L4, CUDA, TensorFlow, PyTorch). Familiarity with container lifecycle management, GPU scheduling, and scaling AI jobs in Kubernetes. Advanced knowledge of Linux systems administration (Ubuntu/Debian), shell scripting, and performance tuning. Deep knowledge of Bare Metal and Virtualized environments. Ability to communicate complex technical topics clearly to customers and cross-functional stakeholders. Experience troubleshooting full-stack deployments—containers, orchestration, networking, and storage. Comfortable working independently and collaboratively in a remote environment. Bonus Points For
Familiarity with cloud-native observability stacks (Prometheus, Grafana, OpenTelemetry). Hands-on experience with Paperspace, JupyterHub, Kubeflow, or Ray. Exposure to networking topics like CNI plugins, overlay networks, and ingress controllers. Prior experience in customer-facing roles at IaaS/PaaS providers or ML Ops platforms. Why You’ll Like Working for DigitalOcean
We innovate with purpose. We prioritize career development. We care about your well-being. We reward our employees. We value diversity and inclusion. Salary range for this position is $87,200 - $109,000 based on market data, relevant years of experience, and skills. DigitalOcean is an equal-opportunity employer and recognizes that diversity of thought and background builds stronger teams and products to serve our customers.
#J-18808-Ljbffr
Act as a technical subject matter expert (SME) for Kubernetes, AI/ML workloads, and GPU-backed infrastructure. Troubleshoot and resolve advanced support cases related to orchestration, performance tuning, container networking, and GPU-based compute. Engage directly with our strategic and high-value customers via tickets, Slack, email, and live sessions. Partner with Engineering and Product teams to provide feedback on platform usability, bugs, and customer needs. Help shape internal runbooks, SOPs, and documentation to scale AI/ML and GPU-related support. Participate in incident management, root cause analysis, and retrospective reviews. Contribute to the architecture and optimization of customer workloads for high availability and cost efficiency. Educate and mentor internal team members on Kubernetes and GPU-based architectures. Influence roadmap priorities by surfacing recurring pain points and opportunities. Requirements
5+ years in technical support, DevOps, solutions engineering, or SRE roles. Deep experience with Kubernetes (preferably CKA-certified) in production environments. Experience supporting AI/ML workflows using GPUs (e.g., NVIDIA A100, L4, CUDA, TensorFlow, PyTorch). Familiarity with container lifecycle management, GPU scheduling, and scaling AI jobs in Kubernetes. Advanced knowledge of Linux systems administration (Ubuntu/Debian), shell scripting, and performance tuning. Deep knowledge of Bare Metal and Virtualized environments. Ability to communicate complex technical topics clearly to customers and cross-functional stakeholders. Experience troubleshooting full-stack deployments—containers, orchestration, networking, and storage. Comfortable working independently and collaboratively in a remote environment. Bonus Points For
Familiarity with cloud-native observability stacks (Prometheus, Grafana, OpenTelemetry). Hands-on experience with Paperspace, JupyterHub, Kubeflow, or Ray. Exposure to networking topics like CNI plugins, overlay networks, and ingress controllers. Prior experience in customer-facing roles at IaaS/PaaS providers or ML Ops platforms. Why You’ll Like Working for DigitalOcean
We innovate with purpose. We prioritize career development. We care about your well-being. We reward our employees. We value diversity and inclusion. Salary range for this position is $87,200 - $109,000 based on market data, relevant years of experience, and skills. DigitalOcean is an equal-opportunity employer and recognizes that diversity of thought and background builds stronger teams and products to serve our customers.
#J-18808-Ljbffr