DigitalOcean
Overview
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. What You’ll Do
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. What You’ll Add To DigitalOcean
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. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions. We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development. We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences. We reward our employees. The salary range for this position is $81,400 - $101,800 based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program. We value diversity and inclusion. We are an equal-opportunity employer, and recognize that diversity of thought and background builds stronger teams and products to serve our customers. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. This is a remote role Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology, Customer Service, and Engineering Industries: Internet Publishing Referrals increase your chances of interviewing at DigitalOcean by 2x This description is focused on the Cloud Support Engineer role and responsibilities at DigitalOcean.
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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. What You’ll Do
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. What You’ll Add To DigitalOcean
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. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions. We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development. We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences. We reward our employees. The salary range for this position is $81,400 - $101,800 based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program. We value diversity and inclusion. We are an equal-opportunity employer, and recognize that diversity of thought and background builds stronger teams and products to serve our customers. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. This is a remote role Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology, Customer Service, and Engineering Industries: Internet Publishing Referrals increase your chances of interviewing at DigitalOcean by 2x This description is focused on the Cloud Support Engineer role and responsibilities at DigitalOcean.
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