Forward Deployed Engineer, Life Sciences

🔥 2 minutes ago

🇩🇪 Germany – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 11%

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Domino Data Lab

WebsiteLinkedInAll Job Openings

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.

📋 Description

• Master Domino platform mechanics and core user/admin functionalities during onboarding • Shadow customer environments and pair with a senior Forward Deployed Engineer • Take full ownership of strategic life sciences customer engagements • Execute independently against a prioritized backlog managed by the Engagement Manager • Build and deploy production-grade solutions across the MLOps lifecycle, including development, deployment, and monitoring • Advise data science teams on Domino best practices • Lead and advise key accounts as a trusted advisor to technical and business stakeholders • Author reusable playbooks, integration templates, and deployment guides • Improve delivery speed across the Forward Deployed Engineer practice • Translate field intelligence into product feedback for SRE, Support, and Product teams • Build and deploy AI solutions including inferencing workflows, cloud and data integrations, interactive applications, Statistical Computing Environments, and clinical CRM solutions

🎯 Requirements

• Strong engineering roots with deep proficiency in Python • Familiarity with SQL, R, and Bash • Experience with Kubernetes and managed Kubernetes solutions such as EKS, AKS, or GKE • Experience with Docker and cloud architecture on AWS, Azure, or GCP • Ability to troubleshoot networking, compute, and platform issues • Proven track record delivering machine learning workflows, model deployment and monitoring, GPU workloads, and generative AI or agent frameworks • Experience operating within or consulting for highly regulated or constrained environments • Ability to navigate strict compliance rules, data security hurdles, and infrastructure limits • Exceptional communication skills across technical and business audiences • Comfortable running structured discovery conversations and leading technical solutioning sessions • Ability to translate customer requirements into buildable, tested solutions • Action-first, ownership-oriented approach; comfortable with ambiguity and unfamiliar codebases

🏖️ Benefits

• Encouragement of diversity and inclusion across backgrounds, genders, ethnicities, abilities, and sexual orientations • Growth mindset and opportunities for teaching and learning • Environment emphasizing employee development and equipping employees with tools for success

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