Machine Learning Researcher - Agentic Science (Fully Remote)

Develop the agentic research vertical at PostEra, using agentic systems to automate mechanistic models for biochemical and physiological processes. Build machine learning methods that rapidly adapt to new drug discovery problems from limited labeled data. Drive the full research loop: defining tasks, constructing datasets and evaluation episodes, training and scaling models, and translating methods into capabilities for scientists. Key Responsibilities: Develop and benchmark agentic systems to automate quantitative model development and biological data analysis. Independently lead research projects in in-context learning, agentic systems, few-shot adaptation, and molecular machine learning. Collaborate cross-functionally with medicinal chemists and biologists to connect modeling objectives to practical drug discovery decisions. Key Requirements: PhD in machine learning or a STEM field involving novel ML approaches, with a track record of high-quality research. Strong research and engineering experience in modern ML, deep learning, or statistical modeling, with hands-on skills in Python and frameworks like PyTorch or JAX. Ability to independently translate ambiguous scientific problems into well-defined ML projects and design careful experiments and benchmarks. PostEra PostEra is building an AI-first biotech, using its Proton AI platform to accelerate the discovery of new medicines for patients. The company has a minimalist organizational structure, celebrating individual achievement through proportional compensation and collaboration toward delivering cures. #J-18808-Ljbffr PostEra