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Scientist I – ML/AI Foundational Models for Synthetic Enhancer Design

allen institute • United State
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AI Summary

Build and maintain an open-source codebase for training and serving genomic sequence-to-function models for synthetic enhancer design. Scale large-scale model training on multi-GPU cloud infrastructure and implement active-learning loops using experimental screening data. Requires a Ph.D. in a related field, strong Python software engineering skills, and experience with deep learning frameworks like PyTorch or JAX.

Key Highlights
Develop open-source tools for genomic sequence models and synthetic enhancer design
Scale deep learning training across cloud GPU infrastructure
Implement active-learning loops integrating in vivo screening results

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Key Responsibilities
Build and maintain an open-source codebase for training, fine-tuning, and serving genomic sequence models
Train large-scale whole-brain models efficiently in multi-GPU cloud environments
Turn cross-species multi-omic data into reproducible, versioned training sets
Implement active-learning loops that feed in vivo screening results back into the next round of models
Publish and present findings in peer-reviewed journals and at scientific conferences
Technical Skills Required
Python PyTorch Deep Learning

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Benefits & Perks
Medical, dental, vision, and basic life insurance
401k plan
Paid time off
Relocation assistance
Visa sponsorship

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Nice to Have
Experience with genomic sequence models (Enformer, Borzoi, AlphaGenome, ChromBPNet, CREsted)
Experience with experiment tracking platforms such as Weights & Biases or MLflow
Experience with cloud platforms and with containers (Docker, Singularity/Apptainer) and workflow managers (Nextflow, Snakemake)
Experience with active learning, Bayesian optimization, or reinforcement learning approaches to model fine-tuning
Experience with the use of AI-assisted coding tools in a development workflow
Experience releasing and maintaining open-source scientific software
Familiarity with gene regulation, chromatin accessibility data, or single-cell genomics
Experience contributing to large, collaborative consortium projects and shared open data resources
Strong written and verbal communication skills, including the ability to explain technical tradeoffs to experimental biologists

Job Description

The accelerates science for a healthier world through large-scale research designed to answer some of the most complex questions in biology. Our multi-disciplinary teams generate foundational knowledge, tools, and data to understand how our brain, cells, and immune system work. We share our work openly so others can build on it, move faster, and ask bigger questions. We drive discovery forward and create new possibilities for improving human health.
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Job Overview
Posted Date Oct 06, 2026
Employment Type Full-time
Experience Level Associate
Location United State
Category Machine Learning
Company allen institute
Mentioned Skills
python ai docker deep learning cloud tensorflow pytorch mlflow

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