
201 - 500 employees
Founded 2013
🤖 Artificial Intelligence
🏢 Enterprise
☁️ SaaS
💰 Series F on 2022-06
Artificial Intelligence • Enterprise • SaaS
Domino Data Lab is a company that empowers AI-driven enterprises to build and manage AI at scale through its Enterprise AI Platform. The platform provides an integrated experience for model development, MLOps, collaboration, and governance, enabling global enterprises to innovate across various sectors. Domino supports better medicinal development, productive agriculture, and competitive product creation. Established in 2013 and backed by notable investors like Sequoia Capital and NVIDIA, Domino enables companies to optimize AI deployment effectively.
🔥 13 hours ago
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201 - 500 employees
Founded 2013
🤖 Artificial Intelligence
🏢 Enterprise
☁️ SaaS
💰 Series F on 2022-06
Artificial Intelligence • Enterprise • SaaS
Domino Data Lab is a company that empowers AI-driven enterprises to build and manage AI at scale through its Enterprise AI Platform. The platform provides an integrated experience for model development, MLOps, collaboration, and governance, enabling global enterprises to innovate across various sectors. Domino supports better medicinal development, productive agriculture, and competitive product creation. Established in 2013 and backed by notable investors like Sequoia Capital and NVIDIA, Domino enables companies to optimize AI deployment effectively.
• Own enterprise customer support cases across all severity levels from initial triage through resolution • Diagnose and resolve Kubernetes and cloud infrastructure issues, including pod failures, resource limits, persistent volumes, RBAC, ingress, and cluster-level diagnostics • Troubleshoot ML platform problems including workspace and job failures, environment build errors, model deployment issues, and data connector failures • File detailed bug reports and enhancement requests in Jira • Advocate for customers with Product and Engineering • Write and review knowledge base articles, how-to guides, and troubleshooting documentation • Hand off cases across AMER, EMEA, and APAC in a follow-the-sun model • Run live troubleshooting sessions with customers via video call • Participate in the EMEA weekend on-call rotation
• 3 to 5 years in enterprise technical support, solutions engineering, or a similar customer-facing technical role at a SaaS or data/AI platform company • Hands-on Kubernetes: pod lifecycle, kubectl, RBAC, namespaces, persistent volumes, and cluster-level troubleshooting • Strong Linux and command-line proficiency: log analysis, process management, file system navigation, and shell scripting • Familiarity with Python-based ML workflows: Jupyter, package management, model training and serving • Experience with cloud platforms (AWS, GCP, or Azure) and containerized application environments • Methodical troubleshooting approach • Clear written communication • Ability to manage multiple open, time-sensitive cases • Ability to work asynchronously across time zones in a remote-first, globally distributed team • Bachelor's degree in computer science, engineering, or a related technical field (or equivalent experience)
• Diverse, inclusive workplace encouraging applicants of all backgrounds • Environment of teaching and learning with tools for employee success • Remote-first, globally distributed team • EMEA weekend on-call rotation per team schedule
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