Engineer, AI​/ML & Analytics Platform Engineering

Overview

At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking medicines that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain 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. Does this inspire you and feel like a fit? Then we would love to have you join us!

At Genmab, AI & analytics technology powers the R&D, Commercial, and functional business units that work to save lives and bring valuable treatments to patients around the world. The AI & Analytics Platform Engineering & Standards team is building quickly to meet the business demand of immediate, real-time, in-house built technology innovation. Our technology experts tackle exciting challenges in collaborative teams while valuing individual and career development.

Our team builds new and innovative systems, creates programs founded in automation in agile frameworks, and drives existing and cutting-edge innovation.

We are seeking an experienced AI/ML & Analytics platform engineer who is passionate about data, digital, and AI. This role secures the efficient and compliant operations of our developer platform, ensuring successful value delivery to Genmab's business. This role is based out of our Princeton or Copenhagen office and requires on-site presence 60% of the time.

You are highly technical and hands-on, building 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 and align 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 the platform to ease of use and efficiency for end-users. You embody the idea that good platform engineering is rarely seen, only felt. You have an automation-first mindset, are security-conscious, and keen on improving the in-house developer experience.

• 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

• Bachelors or Masters 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 in 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 frameworks like PyTorch or Tensor Flow
• Experience with the AWS cloud-service ecosystem including AI/ML & Analytics related services (e.g. Sagemaker, etc.)
• Experience implementing IaC (Terraform, Open Tofu, CDK, Pulumi, etc.) + CI/CD for deploying cloud-based platform infrastructure at scale
• Knowledge of basic software development tools including VCS (Git Hub, Git Lab, etc.), CI/CD (Git Hub/Lab Actions, Jenkins, etc.), JIRA
• Knowledge of containerization (e.g. Docker, Podman, etc.) and orchestration tools (e.g. Kubernetes, Rancher, etc.)
• Experience with large scale CPU, GPU and/or multi-GPU infrastructure (bonus for CUDA fundamentals)
• Knowledge of fundamental ops capabilities such as registries, tracking, observability, and monitoring
• Experience analyzing and improving system performance and reducing costs
• Strong communication skills and ability to engage with stakeholders…