Engineer, AI/ML & Analytics Platform Engineering
Listed on 2025-12-22
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Science Manager, Data Analyst
Engineer, AI/ML & Analytics Platform Engineering
Join to apply for the Engineer, AI/ML & Analytics Platform Engineering role at Genmab
Genmab is dedicated to building extraordinary futures by developing antibody products and groundbreaking KYSO antibody medicines that change lives and the future of cancer treatment. We strive to create a global workplace where individuals’ unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees.
Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. While our work is serious and impactful, we also have big ambitions, bring care to pursuing them, and have fun while doing so.
At Genmab, AI & analytics technology powers R&D, Commercial, and functional business units that tirelessly save lives and bring treatments to patients worldwide. The new AI & Analytics Platform Engineering & Standards team is building quickly to meet immediate, real‑time, in‑house technology innovation demand. Our experts tackle exciting challenges in collaborative teams, valuing individual and career development. Team members build new systems and programs founded in automation in agile frameworks, driving existing and cutting‑edge innovation.
We are seeking an experienced AI/ML & Analytics platform engineer passionate about data, digital, and AI. This role is pivotal in ensuring efficient and compliant operations of our developer platform and delivering value to Genmab’s business.
This role is based out of Princeton or Copenhagen, requiring onsite presence 60% of the time.
Position OverviewYou are highly technical and a hands‑on individual who will build out the core features and capabilities of our AI/ML & Analytics developer platform. You will solve technical and architectural challenges to deliver a scalable, secure, and feature‑robust platform. You will work closely with cross‑functional spoke teams to understand current and evolving AI/ML & Analytics needs, aligning platform and feature build‑out.
You will champion self‑service usage patterns for end users and accelerate our use of IaC and Git Ops to build and scale these solutions. You will drive continuous improvements to ease of use and efficiency for end‑users.
You embody the idea that “good platform engineering is rarely ever seen only felt”. You have an automation‑first mindset, are security‑conscious, and keen on improving the in‑house developer experience.
Responsibilities- Contribute to the build out of the AI/ML & Analytics platform, services, and tools (across dev, test, and prod) that accelerate model training, inference, and deployment within our spoke teams.
- Build platform capabilities to support both batch and real‑time workflows at scale with flexible deployment strategies to accommodate varying use cases (e.g., low‑latency predictions, offline model inference).
- Improve platform performance, reduce manual intervention, scale compute, and increase deployment efficiency.
- Work with the foundational cloud teams to ensure platform operational effectiveness, reliability, security and efficiency.
- Work with team members to provide technical guidance and implementations for monitoring systems (e.g., registry, alerting, etc.) and governance frameworks (e.g., regulatory compliance).
- Collaborate with our spoke teams for AI/ML & Analytics system architecture design, deployment pipelines, and solution scaling.
- Bachelor’s or Master’s in a quantitative subject (e.g., Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research) or a related field with 5+ years of experience.
- Experience building AI/ML & Analytics or related platforms for ML Researchers, ML Engineers, Data Scientists, and Data Analysts.
- Experience building scalable self‑service systems or platforms using microservices and/or event‑based services.
- Strong knowledge of commonly used AI/ML & Analytics programming languages such as Python, Spark, SQL or similar, with experience in machine learning…
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