AI Lab Intern

Genmab • Princeton, TX

1d • Hybrid

About The Position

At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody 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. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so. Does this inspire you and feel like a fit? Then we would love to have you join us! Why Genmab Our internship program provides interns with hands-on experience and relevant projects that directly align with our company’s goals. Additionally, we believe our program provides a valuable opportunity to learn, thrive, and build a strong network. We encourage you to review our website to learn why we’re always looking for smart, purpose-led candidates to play a role in our bold, extra[not]ordinary® future. Job Overview Genmab’s AI Lab is an applied team that identifies high-value use cases and builds practical solutions with strong technical rigor and close stakeholder collaboration. The team’s work spans deep learning, computational modeling, modern AI engineering, and internal AI products that support research and development. The AI Lab partners directly with scientific and business teams to turn real problems into working experiments, clear analyses, and useful tools. The AI Lab Intern will contribute to a defined summer project while supporting broader experimentation across Genmab’s AI and data initiatives. Depending on project scope, the intern may focus on LLM-enabled workflows, data analysis, knowledge systems, predictive modeling, or lightweight internal applications that help teams learn faster from data and make better decisions. The intern will work alongside AI engineers, data scientists, and domain experts throughout the summer.

Requirements

• Currently enrolled in a bachelor’s or master’s program in computer science, data science, machine learning, bioinformatics, computational biology, statistics, applied mathematics, biomedical engineering, or a related field.
• Expected academic standing for Summer 2026: rising junior, rising senior, or current master’s student.
• Coursework, research, or project experience in machine learning, deep learning, natural language processing, data analysis, or software engineering.
• Working proficiency in Python and familiarity with common ML tools or libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Git, or Jupyter.
• Strong analytical thinking, curiosity, and the ability to communicate clearly with both technical and non-technical collaborators.
• Interest in applying AI to healthcare, biotechnology, or other real-world scientific problems.

Nice To Haves

• Exposure to large language models, prompt engineering, retrieval-augmented generation, evaluation frameworks, or AI agents.
• Experience working with biological, clinical, chemistry, or other scientific datasets.
• Familiarity with cloud environments, APIs, version control workflows, or building small internal tools for end users.
• Prior internship, lab, hackathon, or open-source experience that demonstrates initiative and ownership.

Responsibilities

• Build, test, and refine AI or machine learning prototypes that address real research, operational, or knowledge-workflow problems.
• Translate ambiguous questions into structured experiments, measurable success criteria, and clear technical recommendations.
• Write high-quality Python code for data preparation, model experimentation, evaluation, and lightweight application development.
• Partner with AI engineers, scientists, and cross-functional stakeholders to gather requirements, validate assumptions, and present results.
• Contribute to experiments involving modern AI techniques such as LLM applications, retrieval systems, agentic workflows, multimodal inputs, or predictive models, depending on project needs.
• Document methods, findings, and tradeoffs in a form that teammates can reuse after the internship ends.
• Apply sound engineering practices around reproducibility, data handling, responsible AI use, and privacy.

What This Job Offers

• Career Level: Intern