# Deep Learning Scientist II, Protein Sciences at Repertoire Immune Medicines

- Company: Repertoire Immune Medicines
- What the company does: Repertoire Immune Medicines is a clinical-stage biotechnology company working to unlock and direct the remarkable power of the human immune system to prevent or treat cancer, as well as autoimmune and infectious disease. Backed by SoftBank VF.
- Company website: https://www.repertoire.com/
- Type: Startups (AI role)
- Level: Mid level
- Location: Remote (US)
- Work setup: Remote
- Pay: $150K to $170K base salary per year (USD)
- Posted: 2026-09-24
- Apply by: 2026-11-08
- Apply: https://repertoireimmunemedicinesinc.applytojob.com/apply/FrcqNiMv7C/Deep-Learning-Scientist-II-Protein-Sciences
- Page: https://www.1752.vc/careers/jobs/repertoire-immune-medicines-deep-learning-scientist-ii-protein-sciences/

## About the role

Repertoire Immune Medicines is a clinical-stage biotechnology company harnessing the power of the human immune system to develop transformative therapies for cancer and autoimmune disease. Using its proprietary DECODE TM platform—which maps the immune synapse between T cell receptors (TCRs) and their antigen targets—Repertoire translates unique biological insights into potent and targeted off-the shelf immune medicines.

## What they're looking for

- PhD in computer science, computational biology or a related quantitative field, with 2-5 years of industry experience in protein engineering and design
- Hands‑on experience with training and fine-tuning protein language models (PLMs) and structure-prediction models, and in the development of applied AI pipelines for biological data
- Ability to reason about protein-protein interactions through rational structure-based approaches, using physics-based methods and machine learning workflows
- Strong programming skills in Python, including multi-GPU training with PyTorch and related libraries
- Proven ability to analyze and model complex, high‑dimensional biological datasets using sound computational and statistical practices to drive novel insights
- Experience working with TCR-pMHC binding is a strong plus