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Last checked Nov 2, 2026.

Essential Skills & Experience

• Academic Foundation: Bachelor's degree in a scientific or quantitative field (Computer Science, Physics, Mathematics, Biology, Chemistry, or related); an advanced degree (MS or PhD) is preferred.
• Applied ML in Science: Demonstrated experience building and maintaining machine learning models in a scientific discipline in an industry setting, including taking models from prototype through validation and maintenance; experience in a life sciences setting is preferred.
• Large-Scale Data Management: Required experience managing large-scale datasets and managing the training of models over them, including data ingestion, cleaning, versioning, and pipeline maintenance at scale.
• Software Engineering: Strong Python programming skills and experience with modern ML frameworks (e.g. PyTorch, JAX) and experiment tracking/data versioning tools (e.g. Weights & Biases).
• Scientific Rigor: Ability to design sound evaluation methodology (e.g. train/test splitting strategies, held-out generalization tests) and to critically interpret model performance against meaningful baselines.

Highly Desired Skills & Experience

• Bioinformatics & Computational Biology: Experience with bioinformatics and computational biology data analysis tools, particularly transcriptomics harmonization and normalization tools (e.g. batch correction, pseudobulking, gene ID mapping/standardization).
• Domain Datasets: Familiarity with public perturbation or drug-sensitivity datasets such as LINCS L1000, GDSC, DepMap, or single-cell perturbation atlases.
• Knowledge Graphs & GNNs: Experience with knowledge graph embeddings or graph neural networks applied to drugs, targets, or cells.
• Cheminformatics: Familiarity with cheminformatics representations (SMILES, InChI keys, PubChem/Cellosaurus identifiers) used to harmonize drug and cell metadata across datasets.
• Collaborative Innovation: Experience working in interdisciplinary environments where AI intersects with the biological sciences.

Why Join Us?

We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth.

• Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.
• Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits.
• Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
• Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.

SandboxAQ Welcomes All

We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.

Equal Employment Opportunity : All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.

Accommodations : We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.

Read: Guidance for candidates on using AI Tools in interviews