Biomedical AI Lead

Overview

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose.

We’ve been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges.

Position Summary

Credence has an immediate need for a Biomedical AI Lead to join our growing AI and Automation practice and to build and direct a portfolio of biomedical AI research. The position includes existing NIH-funded work, along with responsibility for identifying and pursuing new funding opportunities. Central to the role is establishing collaborations across academia, industry, and government to address high-impact research questions. On the technical side, you will lead teams of ML engineers and data scientists while contributing heavily to building and evaluating models yourself.

The work spans multimodal AI models that integrate diverse biomedical and clinical data (medical imaging, electronic health records, etc.), along with foundation models and LLMs applied to a range of scientific areas. The position offers the intellectual freedom of a research faculty appointment, along with a deep bench of engineering talent, a proposal team to support your efforts, and compensation that reflects your expertise. You will publish and present your work, partner with leading institutions, and shape your own research agenda.

Responsibilities include, but are not limited to the duties listed below

• Directing a portfolio of biomedical AI research.
• Identifying new funding opportunities, forming collaborations, and developing proposals.
• Generating preliminary data and proof-of-concept results to strengthen proposals and launch new research initiatives.
• Developing multimodal AI models that integrate diverse biomedical and clinical data, such as medical imaging and electronic health records. Performing hands-on model development, including data preparation, architecture design, training, and evaluation.
• Providing AI technical leadership on current and future projects, guiding technical approach and execution while managing and mentoring teams of ML engineers and data scientists.
• Publishing and presenting research in peer-reviewed journals and at scientific conferences, and contributing to white papers and technical reports.
• Communicating results to federal sponsors and partners.
• Tracking emerging methods and advances in AI and biomedical science.