Forward Deployed Engineer, Life Sciences

🕒 vor 1 Monat

🇺🇸 Vereinigte Staaten – Remote

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

👷🏻‍♀️ Ingenieur

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

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Domino Data Lab

WebsiteLinkedInAlle Stellen

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.

Beschreibung

• You will be given the resources to master Domino platform mechanics and learn core user/admin functionalities. You will closely shadow the customer’s environment, pairing with a senior FDE to learn the client’s unique data, tooling stack, and commercial objectives. • You will step into full customer ownership across your engagements, executing independently against a prioritized backlog managed by your partner Engagement Manager (EM). You will build and deploy production-grade solutions across the entire MLOps lifecycle (development, deployment, and monitoring) while actively advising data science teams on Domino best practices. • You will lead and advise on key accounts, serving as a trusted advisor to technical and business stakeholders alike. You will author reusable playbooks, integration templates, and deployment guides for our shared knowledge base, measurably lifting the delivery speed of the entire FDE practice. Additionally, you will translate field intelligence into critical product feedback, routing platform signals to our SRE, Support, and Product teams to shape Domino’s roadmap.

🎯 Anforderungen

• Strong engineering roots with deep proficiency in Python (primary), alongside familiarity with SQL, R, and Bash. • Experience with Kubernetes and managed K8s solutions (such as EKS, AKS, or GKE), Docker, and cloud architecture (AWS, Azure, or GCP). You should be capable of troubleshooting networking, compute, and platform issues. • A proven track record of delivering machine learning workflows, model deployment/monitoring, GPU workloads, and generative AI or agent frameworks. • Experience operating within, or consulting for, highly regulated or constrained environments. You can expertly navigate multi-factor constraints like strict compliance rules, data security hurdles, and infrastructure limits. • Exceptional communication skills across both technical and business audiences. You are comfortable running structured discovery conversations, leading technical solutioning sessions, and translating messy customer requirements into buildable, tested solutions. • An "act fast, own it" mentality. You thrive in ambiguity, do not let blockers sit, and are comfortable making yourself productive inside an unfamiliar codebase quickly.

🏖️ Vorteile

• We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply • We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success • We believe in individuals who seek truth and speak the truth and can be their whole selves at work • We value all of you that believe improving is always possible. At Domino, everything is a work in progress – we can do better at everything • We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company