Domino Data Lab provides a platform that utilizes data science and AI for collaboration, model deployment, and centralizing infrastructure.
This company offers a hybrid work model combining remote and office work.
Domino Data Lab empowers the world's largest, AI-driven enterprises to build, deploy, and manage AI at scale. Their Enterprise AI Platform acts as a central system of record for data science teams, integrating tools, compute, and data. You will help accelerate breakthroughs for customers like Johnson & Johnson, Dell Technologies, and the US Navy. They trust Domino to industrialize AI, driving innovation while managing costs and ensuring compliance. Founded in 2013, Domino Data Lab has raised $224 million across 9 funding rounds, backed by leading investors including Sequoia Capital and NVIDIA.
Domino Data Lab embraces a hybrid work model, blending in-office collaboration with remote flexibility. They actively support work-from-home requests, offering a $500 stipend for new employees to set up their home offices. Job postings show openings for "Remote US" and "Remote Argentina." They foster a culture that values a growth mindset and continuous improvement, believing that everything is a work in progress. Expect an environment of teaching and learning, where you are equipped with tools for success. They champion diversity, encouraging applicants from all backgrounds, genders, ethnicities, abilities, and sexual orientations.
Engineers at Domino Data Lab solve complex challenges in AI and MLOps. They build internal AI-assisted reliability tooling that analyzes tickets, logs, traces, and documentation to resolve outages faster. You will modernize CI/CD pipelines, expanding automation coverage and integrating AI-assisted coding tools like Claude, Codex, or Cursor. Projects span scalable back-end systems in distributed computing environments, leveraging Kubernetes, cloud platforms (AWS, Azure, GCP), and observability stacks like Prometheus and New Relic. You will also work with ML model deployment, registries, versioning, and lifecycle management tools, impacting how enterprises develop and operationalize AI.