Machine Learning Engineer (AI/BioSim)

Location: Remote within the United States

Salary: $134,400–$252,000 annual base salary, based on US geographic pay tiers

Company

SandboxAQ develops AI solutions and Large Quantitative Models for life sciences, financial services, navigation, cybersecurity, and other sectors.

What you will do

• Build, train, and maintain machine learning models for transcriptomic response, cell viability, IC50, and toxicity dose-response prediction.
• Acquire, harmonize, normalize, deduplicate, and manage large biological datasets including LINCS L1000, GDSC, Tahoe-100M, and DILImap.
• Develop and harden end-to-end evaluation pipelines with robust statistical baselines and held-out generalization tests.
• Translate research on transformer-based perturbation models, knowledge graphs, and graph neural networks into tested production code.
• Collaborate with computational biologists, software engineers, and product stakeholders to support drug discovery workflows.
• Document methods, assumptions, and results for technical and non-technical audiences.

Requirements

• Bachelor’s degree in computer science, physics, mathematics, biology, chemistry, or a related scientific or quantitative field.
• Experience building and maintaining machine learning models in a scientific industry setting, from prototyping through validation and maintenance.
• Experience managing large-scale datasets and model training pipelines, including ingestion, cleaning, versioning, and maintenance.
• Strong Python skills with modern machine learning frameworks such as PyTorch or JAX, plus experiment tracking or data versioning tools.
• Ability to design rigorous evaluation methodologies and interpret model performance against meaningful baselines.
• Experience with bioinformatics, computational biology, transcriptomics, cheminformatics, or drug and cell metadata harmonization.

Nice to have

• Advanced degree such as an MS or PhD.
• Experience with LINCS L1000, GDSC, DepMap, or single-cell perturbation datasets.
• Knowledge graph embeddings or graph neural networks applied to drugs, targets, or cells.
• Experience in interdisciplinary AI and biological science environments.

Culture & Benefits

• Flexible remote work arrangements within the United States.
• Medical, dental, and vision coverage with employer premium contributions.
• Retirement savings with company matching, paid parental leave, and family-building benefits.
• Flexible paid time off and company-wide seasonal breaks.
• Performance-based incentives or bonuses, equity participation, and learning and development opportunities.