
201 - 500 Mitarbeiter
Gegründet 2013
🤖 Künstliche Intelligenz
🏢 Unternehmen
☁️ SaaS
💰 Series F im 2022-06
Artificial Intelligence • Enterprise • SaaS
Domino Data Lab ist ein Unternehmen, das KI-gesteuerte Unternehmen befähigt, KI in großem Maßstab zu entwickeln und zu verwalten, indem es eine Enterprise AI-Plattform bereitstellt. Die Plattform bietet eine integrierte Erfahrung für Modellentwicklung, MLOps, Zusammenarbeit und Governance, um globalen Unternehmen Innovationen in verschiedenen Sektoren zu ermöglichen. Domino unterstützt die Entwicklung besserer Medikamente, eine produktive Landwirtschaft und eine wettbewerbsfähige Produktentwicklung. Gegründet im Jahr 2013 und unterstützt von namhaften Investoren wie Sequoia Capital und NVIDIA, ermöglicht Domino Unternehmen eine effektive Optimierung der KI-Bereitstellung.
🕒 vor 2 Tagen
🗣️🇺🇸🇬🇧 Englisch erforderlich
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201 - 500 Mitarbeiter
Gegründet 2013
🤖 Künstliche Intelligenz
🏢 Unternehmen
☁️ SaaS
💰 Series F im 2022-06
Artificial Intelligence • Enterprise • SaaS
Domino Data Lab ist ein Unternehmen, das KI-gesteuerte Unternehmen befähigt, KI in großem Maßstab zu entwickeln und zu verwalten, indem es eine Enterprise AI-Plattform bereitstellt. Die Plattform bietet eine integrierte Erfahrung für Modellentwicklung, MLOps, Zusammenarbeit und Governance, um globalen Unternehmen Innovationen in verschiedenen Sektoren zu ermöglichen. Domino unterstützt die Entwicklung besserer Medikamente, eine produktive Landwirtschaft und eine wettbewerbsfähige Produktentwicklung. Gegründet im Jahr 2013 und unterstützt von namhaften Investoren wie Sequoia Capital und NVIDIA, ermöglicht Domino Unternehmen eine effektive Optimierung der KI-Bereitstellung.
• Own the customer program end-to-end: from contract signature through expansion. You're accountable for outcomes, not activities, and every engagement you lead has a single owner (you), clear milestones, and a cadence that keeps everyone (internally and externally) moving as the program manager • Partner with account team to ensure every engagement is scoped to be delivered with excellence, bridging what is sold with what can be executed • Direct the delivery pod (our Forward Deployed Engineers and Integration & Architecture teams) for customer engagements. Put capacity where it creates the most value and keep programs on track across milestones, stakeholder communication, and account health • Earn trust at every level: from C-suite sponsors to the data scientists running models in production. You close the gap between strategic intent and day-to-day delivery • Lead the room in solutioning conversations: connect how Domino builds, scales, and governs AI to the outcomes customer leadership actually cares about. You operate as a peer, not a vendor • Make adoption real: drive rollout, enablement, and change management so what your team ships gets used, not shelved • Turn customer engagements into growth in partnership with customer success and sales — proactively uncovering new use cases and expansion opportunities, qualifying them, and routing them back to internal teams to fuel pipeline • Be the customer's voice inside Domino: convert field intelligence into product feedback, escalations, and commercial signals that make the broader team smarter
• 4–8 years in an enterprise customer-facing discipline: implementations, consulting, technical program management, or product. Caliber and complexity matter more than the title • You move before the problem is fully formed: comfortable when the customer can't yet articulate what's wrong and treating ambiguity as the starting point • You turn unstructured executive conversations into executable plans: connecting model development, deployment, and governance without losing what actually matters • You know enough about how enterprise data science teams build, scale, and govern models to ask the right questions before the customer knows they need to answer them • Real delivery ownership across full cycles, not coordination. You hold an execution rhythm, hold a position when things get hard, and don't create bureaucracy to do it • Experience leading a team: direct reports, a cross-functional pod, or a mix of engineers and specialists. You set direction, develop people, and hold accountability without micromanaging • Technically fluent across software architecture, predictive modeling, and agentic systems: able to get hands-on when it matters and learn new domains fast • Solutions-oriented by default. You escalate with a recommendation, not just a problem, and reach for AI to do all of it faster and better • Background in life sciences, financial services, or a regulated industry where reproducibility, auditability, and compliance are non-negotiable is a meaningful advantage.
• equity • company bonus or sales commissions/bonuses • 401(k) plan • medical, dental, and vision benefits • wellness stipends.
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