AI Scientist: Precision Oncology Foundation Models

Breakout Ventures; United States; Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Hybrid work model

Stock options

Competitive compensation

Job summary

Noetik is seeking a senior ML researcher to lead the development of foundation models that fuse biology and AI. You will publish, present at leading conferences, and collaborate with biologists and partners to push AI-driven drug discovery forward.

Join a highly technical, interdisciplinary team in a hybrid SF setting. You will train large models, evaluate novel architectures, and contribute to the growth of Noetik’s AI-first approach to oncology.

Qualifications

• Publications in top ML journals and conferences (e.g. NeurIPS, ICML)
• Experience writing model architecture code and datasets in PyTorch; training and optimizing models
• Deep knowledge of modern ML architectures and self-supervised learning approaches

Responsibilities

• Design, implement, and train foundation models that integrate biology across spatial scales and measurement modalities
• Identify meaningful benchmark tasks and evaluations for biology foundation models and evaluate open source alternatives
• Own research projects from conception to execution, communicate results to the team and partners
• Integrate with the AI x Bio community, present at conferences and contribute to writeups
• Evaluate use of LLMs to interface with internal foundation models and accelerate research
• Rapidly iterate on research ideas and choose high-leverage experiments

Skills

Publications & talks

PyTorch coding

DL architectures

Distributed systems

Tools

Ray / PyTorch Lightning

Job description

Noetik is seeking a senior ML researcher to lead the development of foundation models that fuse biology and AI. You will publish, present at leading conferences, and collaborate with biologists and partners to push AI-driven drug discovery forward.

Join a highly technical, interdisciplinary team in a hybrid SF setting. You will train large models, evaluate novel architectures, and contribute to the growth of Noetik’s AI-first approach to oncology.