Senior Machine Learning Scientist

Position Summary: We are looking for a Machine Learning Scientist to build AI and machine learning systems that turn complex biological data into actionable scientific insight. You will work at the intersection of ML, genomics, causal biology, and target discovery. The role includes building models, agentic AI workflows, systems that help automate analysis, reasoning, and decision support, and AI assisted tools that help connect genotype, cell state, perturbation, phenotype, and disease mechanism. This is a hands-on role for someone who enjoys writing clear, reliable code, uses modern AI tools to move faster, and wants their work to shape real biological and therapeutic decisions. Responsibilities: Build ML models for genomic, single-cell, perturbation, and phenotype data. Develop agentic AI workflows that help scientists analyze data, test hypotheses, and make better decisions. Use AI coding tools to accelerate development while keeping code reliable, readable, tested, and reproducible. Train and fine tune foundation models, language models, and representation learning methods for target discovery. Model relationships between genotype, cell state, perturbation response, causal biology, and disease. Collaborate closely with computational scientists, experimental biologists, software engineers, and target discovery teams. Communicate results clearly, including model assumptions, limitations, and next steps. Qualifications: You do not need to meet every item to apply. Strong candidates may come from academia, industry, open-source work, or hands-on research. PhD, Master’s degree, or equivalent experience in machine learning, computer science, computational biology, genomics, bioinformatics, statistics, engineering, or a related field. Strong Python coding skills and experience building practical Deep Learning ML systems. Experience using AI coding tools, coding assistants, LLM-based workflows, or agentic development tools. Experience training, evaluating, or applying