[Hiring] Senior Scientist, Machine Learning Research @A-Alpha Bio

Role Description

A-Alpha Bio is seeking a Senior Scientist, Machine Learning Research to turn large-scale protein interaction data into insights and models that advance antibody and protein engineering. The role focuses on developing innovative AI/ML methods that learn from millions of protein-protein interaction data points to predict and engineer protein binding. The Senior Scientist will take a technical lead on challenging AI/ML projects within the ML Research team, including:

• De novo design of antibodies or minibinders.
• Models for affinity prediction and developability optimization.
• Collaboration with other ML Scientists to design and execute experiments (both in silico and in vitro with the help of wet-lab colleagues).
• Support long-term AI/ML research initiatives.
• Communicate scientific results to the ML Research team, broader company, and external collaborators.

Qualifications

• PhD in a quantitative or life sciences field (biology, chemistry, physics, computer science, etc.) with 4+ years of professional experience in software development and AI/ML, including 2+ years of hands-on experience with AI/ML using biological sequence and/or structure data; or Bachelor's degree in a quantitative or life sciences field with 12+ years of relevant experience, including 6+ years of professional experience in software development and AI/ML; or an equivalent combination of education and experience.
• Strong experience with deep learning, spanning modern software frameworks (PyTorch, JAX), model architectures and approaches (variational autoencoders [VAEs], transformers, graph neural networks [GNNs], diffusion, and flow matching), and common protein engineering tasks (protein language models, inverse folding, and protein structure prediction).
• Strong proficiency with data science best practices, including wrangling and transforming data, model training, model selection, cross-validation, and deployment at scale.
• Excellent verbal and written communication skills, including the ability to explain methods, findings, and limitations to computational and experimental audiences, as well as to external collaborators and partners.

Requirements

• Expertise with cloud computing, particularly Amazon Web Services (AWS).
• Proficiency with best practices using large language models (LLMs) and agentic AI tools to assist in code generation and modeling.
• Experience analyzing large experimental datasets and making scientifically defensible decisions about data quality, statistical methods, and interpretation.
• Thorough understanding of concepts from biology, chemistry, and physics that govern molecular properties and interactions.
• Familiarity with the state of the art in antibody engineering, protein engineering, synthetic biology, or other high-throughput biology environments with particular emphasis on the relationship between sequence, structure, and function.

Benefits

• Starting Salary Range: $164,000 - $206,000 annually.
• Exemption Status: Exempt.
• Location Expectations: Remote-Eligible (expected travel to Seattle HQ once per quarter).
• Opportunity to work in a fast-paced, highly dynamic, and interdisciplinary work environment.
• Supportive team culture that values diversity and meritocracy.