Machine Learning Researcher - Agentic Science

📋 Description

• Develop and benchmark agentic systems to automate the development of quantitative models for
• Independently identify, formulate, and lead research projects involving in-context learning
• Design and train models that adapt to new assays, endpoints, targets, or chemical series using
• Rigorously compare new approaches against strong baselines, curating test cases that deconfound the
• Work with scientists to connect modeling objectives and evaluation metrics to practical decisions
• Develop efficient training and data pipelines and, where appropriate, scale models across large

🎯 Requirements

• PhD degree in machine learning, or STEM research involving the development of novel machine
• Track record of high-quality research, such as publications and open-source contributions.
• Strong research or engineering experience in modern machine learning, deep learning, or statistical
• Demonstrated expertise in at least one relevant area: agentic workflows for science, machine
• Hands-on experience training, debugging, and evaluating ML models in Python using frameworks such
• Ability to independently translate ambiguous scientific or technical problems into well-defined ML

🎁 Benefits

• Salary: 200k - 300k
• Equity: 0.05 - 0.1%
• Minimalist organizational structure
• Proportional compensation and internal recognition
• Meaningful promotions
• Cross-disciplinary collaboration