Senior Machine Learning Scientist

About the role

We are seeking a Senior Machine Learning Scientist to develop AI and machine‑learning systems that transform complex biological data into actionable scientific insight. The role sits at the intersection of machine learning, genomics, causal biology, and target discovery, and directly influences therapeutic decisions.

Key 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 ensuring code reliability, readability, testing, and reproducibility.
• Train and fine‑tune foundation models, language models, and representation‑learning methods for target discovery.
• Model relationships among genotype, cell state, perturbation response, causal biology, and disease.
• Collaborate with computational scientists, experimental biologists, software engineers, and target discovery teams.
• Communicate results clearly, including model assumptions, limitations, and next steps.

Required profile

• 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 experience building practical deep‑learning systems.
• Experience using AI coding tools, coding assistants, or LLM‑based development workflows.
• Demonstrated ability to train, evaluate, or apply ML models to complex real‑world biological data.

Required skills

• Python
• Deep Learning
• Machine Learning model development
• AI coding tools / LLM‑based workflows
• Foundation model training and fine‑tuning
• Representation learning
• Single‑cell genomics analysis
• Perturbation modeling
• Causal inference
• Large‑scale biological data processing