Machine Learning Researcher - Agentic Science

Responsibilities

• Develop and benchmark agentic systems to automate quantitative models for biological and physiological processes
• Lead research projects in in-context learning, few-shot adaptation, and tabular foundation models
• Design models that adapt to new assays and chemical series using limited labeled context
• Collaborate with scientists to connect modeling objectives to practical drug discovery decisions
• Develop efficient training and data pipelines and scale models across molecular tasks
• Produce reproducible research code and publish results in leading ML and computational biology venues

Requirements

• PhD degree in machine learning or STEM research involving novel ML approaches
• Proven track record of high-quality research publications or open-source contributions
• Strong engineering experience in deep learning or statistical modeling
• Expertise in agentic workflows, bioinformatics, in-context learning, or tabular learning
• Hands-on experience with Python and frameworks like PyTorch or JAX
• Ability to design rigorous experiments, benchmarks, and ablations

Preferred Qualifications

• Experience training tabular foundation models for sparse or heterogeneous data
• Experience developing molecular in-context learning systems
• Experience with large model training (1B+ parameters) and distributed training
• Development of AI "co-scientist" systems for physical or biological problems
• Experience moving research models into production scientific software

About the Company

PostEra is an AI-first biotech using its Proton platform for medicinal chemistry to accelerate the discovery of new medicines, focusing on Women's Health, Fertility, and antiviral drug discovery.